WO2020215214A1 - Procédé et appareil de traitement d'image - Google Patents

Procédé et appareil de traitement d'image Download PDF

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Publication number
WO2020215214A1
WO2020215214A1 PCT/CN2019/083920 CN2019083920W WO2020215214A1 WO 2020215214 A1 WO2020215214 A1 WO 2020215214A1 CN 2019083920 W CN2019083920 W CN 2019083920W WO 2020215214 A1 WO2020215214 A1 WO 2020215214A1
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WIPO (PCT)
Prior art keywords
image
image frame
frame
distortion
video
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Ceased
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PCT/CN2019/083920
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English (en)
Chinese (zh)
Inventor
杨曾雄
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SZ DJI Technology Co Ltd
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SZ DJI Technology Co Ltd
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Application filed by SZ DJI Technology Co Ltd filed Critical SZ DJI Technology Co Ltd
Priority to PCT/CN2019/083920 priority Critical patent/WO2020215214A1/fr
Priority to CN201980008888.4A priority patent/CN111684784B/zh
Publication of WO2020215214A1 publication Critical patent/WO2020215214A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N5/00—Details of television systems
    • H04N5/222—Studio circuitry; Studio devices; Studio equipment
    • H04N5/2228—Video assist systems used in motion picture production, e.g. video cameras connected to viewfinders of motion picture cameras or related video signal processing
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/95—Computational photography systems, e.g. light-field imaging systems
    • H04N23/951—Computational photography systems, e.g. light-field imaging systems by using two or more images to influence resolution, frame rate or aspect ratio
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N5/00—Details of television systems
    • H04N5/222—Studio circuitry; Studio devices; Studio equipment
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N5/00—Details of television systems
    • H04N5/222—Studio circuitry; Studio devices; Studio equipment
    • H04N5/262—Studio circuits, e.g. for mixing, switching-over, change of character of image, other special effects ; Cameras specially adapted for the electronic generation of special effects
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N5/00—Details of television systems
    • H04N5/222—Studio circuitry; Studio devices; Studio equipment
    • H04N5/262—Studio circuits, e.g. for mixing, switching-over, change of character of image, other special effects ; Cameras specially adapted for the electronic generation of special effects
    • H04N5/2621—Cameras specially adapted for the electronic generation of special effects during image pickup, e.g. digital cameras, camcorders, video cameras having integrated special effects capability

Definitions

  • the present invention relates to the field of image processing, in particular to an image processing method and device.
  • users use a camera to record related sports or daily activities, such as cycling, skydiving, skiing, surfing, walking, etc.
  • the video stream obtained by the camera generally restores the real shooting scene.
  • the shooting device in order to obtain a better motion shooting effect, the shooting device is fixed on a mobile device, and the mobile device is moved, so that the shooting device shoots a sports scene.
  • the mobile device moves too fast or too slow, it will cause scenes in the video stream to change too fast or too slowly, and the visual effect of the video stream cannot meet the viewing requirements of the human eye.
  • users can adjust the video playback rate to change the visual effect of the corresponding video stream, such as reducing the video playback rate for a video stream that changes too quickly; for a video stream that changes too slowly To increase the rate of video playback. Adjusting the video playback rate is not only cumbersome, but also difficult to obtain better visual effects.
  • the invention provides an image processing method and device.
  • the present invention is implemented through the following technical solutions:
  • an image processing method including:
  • an image processing device including:
  • Storage device for storing program instructions
  • One or more processors call program instructions stored in the storage device, and when the program instructions are executed, the one or more processors are individually or collectively configured to:
  • a computer-readable storage medium having a computer program stored thereon, and when the program is executed by a processor, the following steps are implemented:
  • a method for enhancing the sense of motion of an image including:
  • a method for enhancing the sense of motion of an image including:
  • a mobile terminal includes:
  • Storage device for storing program instructions
  • One or more processors call program instructions stored in the storage device, and when the program instructions are executed, the one or more processors are individually or collectively configured to:
  • an unmanned aerial vehicle including:
  • Storage device for storing program instructions
  • One or more processors call program instructions stored in the storage device, and when the program instructions are executed, the one or more processors are individually or collectively configured to:
  • a handheld PTZ includes:
  • Storage device for storing program instructions
  • One or more processors call program instructions stored in the storage device, and when the program instructions are executed, the one or more processors are individually or collectively configured to:
  • a photographing device comprising:
  • Image acquisition module for obtaining video files
  • Storage device for storing program instructions
  • One or more processors call program instructions stored in the storage device, and when the program instructions are executed, the one or more processors are individually or collectively configured to:
  • the present invention obtains a second image frame with better visual effects by adjusting the distortion parameters of the image block of the first image frame in the video file, and then uses the second image frame to replace the first image frame.
  • Image frame so that when the video file is played, the motion effect of the image is more in line with the human visual requirements, without adjusting the video playback rate.
  • Fig. 1 is a method flowchart of an image processing method in an embodiment of the present invention
  • FIG. 2 is a relationship curve between distances from different positions to the image center and distortion parameters in a first image frame in an embodiment of the present invention
  • Fig. 3 is a schematic diagram of a division method of image blocks of a first image frame in an embodiment of the present invention
  • 4A is a schematic diagram of the optical flow field of the first image frame in an embodiment of the present invention.
  • 4B is a schematic diagram of the optical flow field of the first image frame in an embodiment of the present invention.
  • 5A is an implementation manner of adjusting the distortion parameter of at least one image block in the first image frame in an embodiment of the present invention
  • 5B is an implementation manner of adjusting the distortion parameter of at least one image block in the first image frame in another embodiment of the present invention.
  • Figure 6 is a structural block diagram of an image processing device in an embodiment of the present invention.
  • Fig. 7 is a method flowchart of a method for enhancing image motion in an embodiment of the present invention.
  • FIG. 8 is a method flowchart of a method for enhancing image motion in another embodiment of the present invention.
  • FIG. 9 is a structural block diagram of a mobile terminal in an embodiment of the present invention.
  • FIG. 10 is a schematic diagram of the structure of an unmanned aerial vehicle in an embodiment of the present invention.
  • FIG. 11 is a structural block diagram of a handheld PTZ in an embodiment of the present invention.
  • Fig. 12 is a structural block diagram of a photographing device in an embodiment of the present invention.
  • the imaging process of the camera is essentially the conversion of the coordinate system.
  • the points in the space are converted from the world coordinate system to the camera coordinate system, and then they are projected onto the imaging plane (image physical coordinate system), and finally the points on the imaging plane
  • the data is converted to the image pixel coordinate system.
  • the distortion of the lens usually includes radial distortion.
  • Radial distortion is the distortion distributed along the radius of the lens. The reason is that the light is more curved away from the center of the lens than near the center. Radial distortion mainly includes barrel distortion and pincushion distortion.
  • the embodiment of the present invention mainly adjusts image parameters (for example, radial distortion) to realize the adjustment of the image motion sense, so that the adjusted image presents different visual effects according to different adjustment parameters.
  • image parameters for example, radial distortion
  • Fig. 1 is a method flowchart of an image processing method in an embodiment of the present invention. As shown in Fig. 1, the image processing method may include the following steps:
  • the video file includes a video frame, and the video frame may include at least one first image frame.
  • the video frame includes a series of first image frames obtained by shooting in time sequence. For example, for a shooting device with a shooting frame rate of 30 fps, the video frame obtained in 1 minute includes the first image frame of 1800 frames.
  • the number of video frames in a video file may include one or more.
  • the video file includes a series of video frames obtained by shooting in time sequence, and the number of first image frames in each video frame may be the same or different. It can be understood that a series of video frames in the video file may also be determined by dividing the same video frame according to the shooting sequence.
  • the video file may include multiple video frames, which are obtained from a single shooting scene in a continuous sequence.
  • the video file may include multiple video frames, but there are two or more video frames in the multiple video frames whose shooting timing is not continuous.
  • the image processing method is applied to an image processing device such as a computer.
  • the video file is sent by an external device, received and processed by the processing device; optionally, the video file is pre-stored in the local disk of the image processing device, and the image processing device is triggered to read the video directly from the local disk file.
  • the image processing method is applied to the shooting device, and the video file is a video file buffered by the shooting device during shooting.
  • the main body of acquiring video files it can be a camera with a camera function, a video camera, a smart phone, a smart terminal, a shooting stabilizer, an unmanned aerial vehicle, etc.
  • the image block is a part of the image frame, for example, it may include an area far from the center of the image in the first image frame.
  • Figure 2 is the relationship curve between the distance from different positions in the first image frame to the image center (ordinate) and the distortion parameter (abscissa), which can be determined from Figure 2.
  • the distance in the first image frame is farther away from the image center The more obvious the radial distortion is in the area of the first image frame, so by adjusting the distortion parameters in the area far from the image center in the first image frame, the visual effect of the image edge can be improved.
  • the first image frame can be divided into multiple image blocks based on different methods, the first image frame can be divided into multiple image blocks based on the field of view; the first image frame can also be divided based on the optical flow field (Optical Flow Vector) For multiple image blocks.
  • optical flow field Optical Flow Vector
  • the first image frame different field of view regions have different distortions.
  • Divide the first image frame into multiple image blocks divide the image blocks according to the law of field of view change, and then adjust the distortion parameters of the image block, the obtained second image frame will be closer to the law of field of view change.
  • the image blocks are distributed on concentric circles with the center of the field of view as the center, and the area far from the center of the image in the first image frame may include the area of the field of view far from the center of the first image frame.
  • the field of view that is farther from the center of the circle corresponds to a larger field of view, so the field of view size can be used as the priority of selecting image blocks for distortion parameter adjustment.
  • the priority of the field of view from large to small is to select the field of view area as the image block for adjusting the distortion parameters to more obviously improve the image visual effect.
  • the difference in radius of the concentric circles corresponding to two adjacent image blocks is a preset difference value, that is, the first image frame is equally divided into a plurality of image blocks.
  • the first image frame can be equally divided into 10 image blocks, from the center of the field of view of the first image frame to the outside of the first image frame, the field of view areas are respectively 0.1 Field (herein referred to as F), 0.2F,..., 0.7F, 0.8F, 0.9F, 1.0F.
  • the radius of the concentric circles corresponding to 0.1F can be set as needed, and the radius difference of the concentric circles corresponding to two adjacent image blocks is a preset difference, and the preset difference is based on the concentric corresponding to 0.1F
  • the radius of the circle and the number of field of view areas to be divided are determined.
  • Figure 3 is an example of dividing the first image frame according to the field of view.
  • the image can be divided equally in the radial area of the field of view, divided according to the area of the field of view, or non-equal. Divide; the number of blocks that can be divided can be 10 image blocks, or other settings can be made for the number of divided blocks.
  • the division granularity of the unequal division can increase from fine-grained to coarse-grained, such as 0.05F, 0.1F, 0.2F, 0.35F, 0.55F,..., this halving method is conducive to the reflection of the image details.
  • the optical flow field of the image obtained by shooting usually presents a certain rule, as shown in FIG. 4A.
  • the optical flow field is generated using a video captured by a camera.
  • Data from sensors associated with the camera can be used to help generate an optical flow field that is useful for encoding video data captured by the camera.
  • the sensor associated with the camera may be on the camera, the support structure of the camera (e.g., UAV), and/or the carrier (e.g., pan/tilt) that supports the camera on the support structure.
  • the sensor associated with the camera may be remote from the camera, the carrier, and/or the support structure of the camera.
  • the optical flow field shows the movement trend of the same pixel between multiple adjacent frames in the video, it can not only be used for video encoding and decoding, but also for dividing image blocks during distortion stretching operations.
  • the photographing device moves forward in a substantially forward manner, and the optical flow field obtained by this movement method is substantially perpendicular to the surface of the photographing device. Based on the optical flow field, the field of view area can be divided in the manner of concentric circles, thereby obtaining a division manner similar to FIG. 3.
  • Figure 4B due to the relative motion of the camera, the optical flow field has a certain degree of curvature. In multiple consecutive frames, the way of dividing the field of view area in each frame will be different.
  • the curvature of the field prediction corrects the segmentation method of the image block.
  • the image block can also be predicted by the feedback parameters of the motion sensor or the image captured by the camera. Segmentation.
  • the support structure of the camera may support one or more sensors.
  • the support structure may be a UAV. Any description of the UAV's sensor can be applied to any type of support structure used for the camera.
  • UAV may include one or more vision sensors, such as image sensors.
  • the image sensor may be a monocular camera, a stereo vision camera, a radar, a sonar, or an infrared camera.
  • the UAV may further include other sensors that can be used to determine the location of the UAV or that may be useful for generating optical flow field information, such as a global positioning system (GPS) sensor, which can be used as part of an inertial measurement unit (IMU) or interact with an inertial measurement unit Separately used inertial sensors (for example, accelerometer, gyroscope, magnetometer), lidar, ultrasonic sensor, acoustic sensor, WiFi sensor.
  • GPS global positioning system
  • IMU inertial measurement unit
  • IMU inertial measurement unit
  • Separately used inertial sensors for example, accelerometer, gyroscope, magnetometer
  • lidar ultrasonic sensor
  • acoustic sensor acoustic sensor
  • WiFi sensor acoustic sensor
  • the UAV may have sensors mounted on the UAV that directly collect information from the environment without contacting additional components for additional information or processing that are not mounted on the UAV.
  • sensors that collect data directly in the environment can be visual sensors or audio sensors.
  • the UAV may have a sensor that is mounted on the UAV but is in contact with one or more components that are not mounted on the UAV to collect data about the environment.
  • the sensor that contacts a component that is not mounted on the UAV to collect data about the environment may be a GPS sensor or another sensor that relies on a connection to another device (such as a satellite, tower, router, server, or other external device) .
  • sensors may include, but are not limited to, position sensors (e.g., global positioning system (GPS) sensors, mobile device transmitters capable of position triangulation), visual sensors (e.g., capable of detecting visible light, infrared light, or ultraviolet light).
  • position sensors e.g., global positioning system (GPS) sensors, mobile device transmitters capable of position triangulation
  • visual sensors e.g., capable of detecting visible light, infrared light, or ultraviolet light.
  • Imaging devices such as cameras
  • proximity sensors or range sensors for example, ultrasonic sensors, lidar, time-of-flight or depth cameras
  • inertial sensors for example, accelerometers, gyroscopes, inertial measurement units (IMU)
  • altitude sensors Posture sensor (for example, compass)
  • pressure sensor for example, barometer
  • audio sensor for example, microphone
  • field sensor for example, magnetometer, electromagnetic sensor
  • Any suitable number and combination of sensors can be used, such as one, two, three, four, five or more sensors.
  • data can be received from sensors of different types (for example, two, three, four, five or more types).
  • Different types of sensors can measure different types of signals or information (for example, position, orientation, speed, acceleration, proximity, pressure, etc.) and/or use different types of measurement techniques to obtain data.
  • the sensor may be associated with the UAV.
  • the sensor can detect the characteristics of the UAV, such as the position of the UAV, the speed of the UAV, the acceleration of the UAV, the direction of the UAV, the noise generated by the UAV, the light emitted or reflected from the UAV, the heat generated by the UAV, or the UAV Any other characteristics.
  • the sensor can collect data, which can be used alone or in combination with sensor data from the UAV to generate optical flow field information.
  • the sensors may include any suitable combination of active sensors (e.g., sensors that generate and measure energy from their own energy source) and passive sensors (e.g., sensors that detect available energy).
  • some sensors can generate absolute measurement data based on the global coordinate system (for example, position data provided by GPS sensors, altitude data provided by a compass or magnetometer), while other sensors can generate absolute measurement data based on local coordinates.
  • Relative measurement data provided by the system for example, the relative angular velocity provided by the gyroscope; the relative translational acceleration provided by the accelerometer; the relative altitude information provided by the visual sensor; the relative altitude information provided by the ultrasonic sensor, lidar or camera during flight Distance information).
  • Sensors mounted or not mounted on the UAV can collect information, such as the location of the UAV, the location of other objects, the orientation of the UAV, or environmental information.
  • a single sensor may be able to collect a complete set of information in the environment, or a group of sensors may work together to collect a complete set of information in the environment.
  • Sensors can be used to map locations, navigate between locations, detect obstacles, or detect targets.
  • the sensor can be used to collect data for generating an optical flow field, which is used to efficiently encode video data captured by a UAV.
  • the UAV can also have an optical flow field generator.
  • the optical flow field generator can be arranged to be mounted on the UAV (for example, in the UAV body or arm, on the camera or on the carrier). Alternatively, the generated optical flow field can be set to not be mounted on the UAV (for example, at a remote server, cloud computing infrastructure, remote terminal, or ground station).
  • the optical flow field generator may have one or more processors that are individually or collectively configured to generate the optical flow field based on sensor data associated with the UAV.
  • the optical flow field shows how light flows within the image frame. This optical flow indicates how the captured object moves between image frames. Specifically, the optical flow field can describe how the object captured by the camera moves.
  • the video captured in the FOV of the camera may include one or more stationary objects or movable objects.
  • the optical flow field can be used to determine the speed or acceleration of objects moving in the video.
  • the optical flow field can also be used to show the moving direction of objects in the video. The following describes examples of optical flow fields with respect to FIGS. 4A and 4B, which describe objects moving within the video.
  • the sensor data used to generate the optical flow field can be obtained by one or more sensors associated with the UAV. Additionally or alternatively, sensor data can be obtained from an external source, such as an external monitoring system.
  • the communication channel can be used to provide external sensor data to the UAV. Therefore, an optical flow field can be generated at the UAV. Alternatively, the optical flow field can be generated outside the UAV.
  • the UAV may provide sensor information associated with the UAV to one or more external processors.
  • the one or more external processors may then use sensor data associated with the UAV to generate the optical flow field.
  • the one or more external processors may provide the generated optical flow field to the UAV.
  • the optical flow field generator (whether mounted or not mounted on the UAV) can receive data from sensors associated with the UAV (whether the sensor is mounted, non-mounted, or any combination of the above) , The data can be used to generate an optical flow field.
  • the sensor data may optionally include information about the spatial layout of the camera (for example, coordinates, translational position, height, orientation) or movement of the camera (for example, linear velocity, angular velocity, linear acceleration, angular acceleration).
  • the sensor data may be able to detect the zoom state of the camera (for example, focal length, zoom in or zoom out). Sensor data may be useful for calculating how the FOV of the camera may change.
  • FIG. 4A and Figure 4B provide examples of optical flow fields.
  • FIG. 4A and FIG. 4B show an optical flow field associated with a magnification feature according to an embodiment of the present invention, and the magnification feature is associated with a photographing device.
  • the magnification feature may occur based on the following situations: the camera magnifies the object; the aircraft's support area that allows the camera to move closer; or a combination of the two.
  • the movement at the edge of the optical flow field is greater than the movement at the middle of the optical flow field.
  • the magnified directivity on the optical flow field is equal. In other words, there is no significant shift in vertical or horizontal distance, because each direction moves in a similar manner.
  • the relationship of the perceived object size in the optical flow field may change based on the position of the object in the optical flow field. For example, when generating an optical flow field based on a zooming action, objects of the same size in real life may appear larger than they are farther from the edge of the optical flow field. This situation is shown in FIGS. 4A and 4B, which show the first sphere 410 close to the normalized minimum at the center of the optical flow field and the second sphere 420 near the periphery of the optical flow field. Although the first ball 410 and the second ball 420 have the same size, they appear to have different sizes when viewed in the background of the optical flow field. Therefore, the perceived object size can change in the optical flow field. Specifically, when an object is placed at different positions on the optical flow field, the perceived object size can be linearly proportional, inversely proportional, or modeled by another equation.
  • the image block is obtained by dividing the optical flow field of the video frame where the first image frame is located, and the distortion parameter of the image block divided according to the optical flow field is adjusted, and the second image frame obtained will be more Close to the changing law of optical flow field.
  • the first image frame is divided into multiple image blocks based on the optical flow fields shown in FIG. 4A and FIG. 4B.
  • the first image frame can also be divided into multiple image blocks based on optical flow fields of other shapes.
  • the same division strategy can be used to divide each first image frame in the video file into multiple image blocks, or different division strategies can be used to divide each first image frame in the video file into multiple image blocks.
  • Image blocks In the following embodiments, the same division strategy is used to divide each first image frame in the video file into multiple image blocks to reduce the difficulty of image processing. Among them, in each first image frame, image blocks with the same position relative to the center of the image may be referred to as image blocks with the same position.
  • the distortion parameter can be adjusted for each first image frame in the video frame, or the distortion parameter can be adjusted for part of the first image frame in the video frame, which is specifically selected according to needs.
  • the video frame obtained by replacing the first image frame with the second image frame is called a new video frame.
  • the distortion parameter is adjusted for each first image frame in the video frame. After the first image frame is replaced by the second image frame, the visual effect of the new video frame is better.
  • the video file includes, for example, a series of video frames obtained by shooting in step S101.
  • the implementation of S102 may include: increasing the distortion parameter size of at least one image block in each first image frame of the video frame (ie, stretching distortion) to generate the corresponding first image Frame the second image frame.
  • the distortion of at least one image block in the first image frame is stretched to achieve the effect of increasing the distortion, so that the acceleration of the first image frame is more intense.
  • the distortion adjustment strategy of the embodiment shown in FIG. 5A is more suitable for sports For video frames with less obvious feeling (slower changes between frames), after the video frames are processed using the distortion adjustment strategy of the embodiment shown in FIG. 5A, the motion feeling of the new video frame is more obvious than that of the unprocessed video frame.
  • the implementation manner of increasing the distortion parameter size of at least one image block in each first image frame of the video frame can also be selected in different implementation manners, for example, a linear manner or a non-linear manner may be used to continuously adjust the shooting sequence.
  • the distortion parameter size of at least one image block in the first image frame of the multiple video frames is increased.
  • the distortion parameter size of at least one image block in each first image frame of the video frame is increased, specifically, the first image frame of the multiple video frames with continuous shooting sequence
  • the distortion parameter size of at least one image block in the image block is sequentially increased, that is, for the image block at the same position in the first image frame in sequential sequence, the distortion parameter size of the image block is sequentially increased in a linear manner according to the shooting sequence.
  • This implementation method adopts this linear method, and the motion acceleration transition of the new video frame is smoother.
  • the distortion parameter size of at least one image block in the first image frame of the multiple video frames with continuous shooting sequence is increased in a non-linear manner, so as to obtain a new, more violent motion acceleration.
  • Video frames the increasing gradient of the distortion parameter size of the image block is determined according to the distortion parameter size of the corresponding image block and the first preset coefficient.
  • the gradient of the distortion parameter size increase of the image block is the product of the distortion parameter size of the corresponding image block and the first preset coefficient, that is, the distortion parameter size of the image block after the distortion parameter size increase processing is: The original distortion parameter size of the image block+the original distortion parameter size of the image block*the first preset coefficient, where the original distortion parameter size of the image block is the distortion parameter size of the image block before the distortion adjustment.
  • the strategy adopted for increasing the gradient of the distortion parameter size of the image block is not limited to the product of the distortion parameter size of the corresponding image block and the first preset coefficient, and may be other.
  • the processing of the distortion parameters may be determined by the movement of the camera, for example, according to the sensor feedback carried by the carrier to determine whether to perform distortion stretching on the image. For example, according to the process of shooting continuous video, while continuously obtaining the parameters obtained by the IMU in time sequence, when the IMU shows that the current camera is not accelerating (the carrier is still or moving at a low speed), the image block is not stretched or Only basic amount of distortion stretching is performed.
  • the magnitude of the distortion blackening stretch is determined by the feedback parameter of the IMU.
  • the IMU shows that the current camera has accelerated motion
  • the distortion stretching ratio can be positively correlated with the data fed back by the IMU. This can enhance the sense of motion of the image while distorting
  • the size of the stretch is consistent with the changes in the data output by the IMU, and the distortion and stretch parameters of the entire video change more smoothly. For the viewer, since the distortion stretch parameters are consistent with the actual motion scene reflected in the video, while the image motion is increased, the viewing effect is more natural.
  • each first image frame has the same strategy for increasing the size of the distortion parameter, so that the effect transition of the distortion stretching within the same video frame is smoother.
  • the position of the image block whose distortion parameter is increased is the same.
  • the 1.0F distortion parameter size of each first image frame in the first video frame is increased, and the 1.0F and 0.9F distortion parameter sizes of each first image frame in the second video frame are respectively processed. Increase processing.
  • the first preset coefficients corresponding to the image blocks at the same position are the same, and the first preset coefficients corresponding to the image blocks at different positions are different, which is increased by using different distortions.
  • the strategy increases the distortion parameter sizes of image blocks at different positions in the first image frame to increase the distortion difference between different positions in the first image frame, thereby enhancing the sense of motion of the first image frame.
  • the first preset coefficients corresponding to image blocks at different positions in each image block whose distortion size is increased are positively correlated with the distance from the image block to the image center, that is, from the image center. The farther the image block corresponds to the larger the first preset coefficient, the more obvious the distortion stretching effect of the corresponding image block, and the enhancement of the sense of motion of the first image frame is realized.
  • the difference between the first preset coefficients corresponding to the image blocks at two adjacent positions in each image block whose distortion size is increased is a preset size, for example, for a certain
  • the first preset coefficient corresponding to 1.0F is 30%
  • the first preset coefficient corresponding to 0.9F is 25%, that is, the preset size is 5%. It is understandable that the preset size It can also be other numerical values.
  • the first preset coefficients corresponding to image blocks at different positions in each image block whose distortion size is increased are positively correlated with the distance from the image block to the image center, and the same In an image frame, the difference between the first preset coefficients corresponding to two adjacent image blocks in each image block whose distortion size is increased is a preset size.
  • the first preset coefficients corresponding to image blocks at different positions in each image block whose distortion size is increased are positively correlated with the distance from the image block to the image center, but In the same first image frame, the difference between the first preset coefficients corresponding to two adjacent image blocks in each image block whose distortion size is increased is not a fixed value.
  • the first image frame between different video frames has different strategies for increasing the distortion parameter size.
  • the distortion parameter size of the first image frame between different video frames is increased.
  • the distortion difference of the first image frame between different video frames thereby enhancing the sense of motion between different video frames.
  • the number of image blocks whose distortion parameter size is increased for the first image frame between different video frames increases successively with the shooting sequence of the video frame, for example, for the first image frame with continuous shooting sequence For the video frame and the second video frame, the shooting sequence of the first video frame is earlier than that of the second video frame, and the number of image blocks whose distortion parameter increases is 1 for the first image frame of the first video frame;
  • the number of image blocks whose distortion parameter size is increased in the first image frame of the video frame is 2.
  • the first image frame between different video frames is subjected to an image block with an increased distortion parameter size to increase along a direction close to the image center, such as a 1.0F distortion for each first image frame in the first video frame
  • the parameter size is increased, and the distortion parameter sizes of 1.0F and 0.9F of each first image frame in the second video frame are respectively increased.
  • the first preset coefficient corresponding to the image block at the same position sequentially increases with the shooting timing of the video frame. For example, for the first video frame and the second video frame whose shooting sequence is continuous, the shooting sequence of the first video frame precedes the second video frame, and the first video frame corresponds to 1.0F of each first image frame in the first video frame.
  • the coefficient is set to 25%, and the first preset coefficient corresponding to 1.0F of each first image frame in the second video frame is 30%, so that the sense of motion between different video frames is enhanced.
  • the lens field of view is divided into four fields of view, 0.9F, 0.8F, 0.7F, and 0.6F, respectively.
  • the video file includes a 1min video frame. If the frame rate is 30fps, the video frame includes 1800 frames of the first image frame.
  • the video frame can be equally divided into 4 segments, namely A segment, B segment, C segment and D segment, each with 450 frames of first image Frames, and the shooting sequence of segments A, B, C and D are consecutive.
  • the following algorithm operations can be performed on each video frame:
  • the distortion parameter size of 0.9F is stretched by 25%, and the other fields of view remain unchanged;
  • the distortion parameter size of 0.9F is stretched by 30%, and the distortion parameter size of 0.8F is stretched by 25%, and the other fields of view remain unchanged;
  • the 4 segments of video frames are deformed and stretched, the 4 segments are recombined and encoded into a new video file.
  • a visual effect of accelerated movement will be presented.
  • 25%, 30%, 35%, and 40% are exemplary values. It can also be set according to the acceleration value fed back by the IMU and the preset coefficient.
  • the stretch value can be changed stepwise between every two adjacent frames.
  • the implementation of S102 may include: reducing the distortion parameter size of at least one image block in each first image frame of the video frame (that is, weakening the distortion) to generate the first image frame corresponding to the first image frame. Two image frames.
  • the distortion adjustment strategy of the embodiment shown in FIG. 5B is more suitable for video frames with a sharper acceleration (faster changes between frames). After the video frame is processed by the distortion adjustment strategy of the embodiment shown in FIG. 5B, the new video frame The acceleration is slower than unprocessed video frames.
  • the size of the distortion parameter of at least one image block in each first image frame of the video frame is reduced to generate a second image frame corresponding to the first image frame.
  • Different implementation methods can also be selected, such as The distortion parameter size of at least one image block in the first image frame of the multiple video frames with continuous shooting sequence can be reduced in a linear manner or a nonlinear manner.
  • the distortion parameter size of at least one image block in each first image frame of the video frame is reduced, specifically, the first image frame of the multiple video frames with continuous shooting sequence is reduced.
  • the distortion parameter size of at least one image block in the image block is sequentially reduced, that is, for the image block at the same position in the first image frame in sequential sequence, the distortion parameter size of the image block is sequentially reduced in a linear manner according to the shooting sequence.
  • the implementation method adopts this linear method, and the acceleration of the new video frame is weakened and the transition is smoother.
  • the distortion parameter size of at least one image block in the first image frame of the multiple video frames with continuous shooting sequence is reduced in a non-linear manner to obtain a new video with reduced acceleration. frame.
  • the gradient of the distortion parameter size reduction of the image block is determined according to the distortion parameter size of the corresponding image block and the second preset coefficient.
  • the gradient of the distortion parameter size reduction of an image block is the product of the distortion parameter size of the corresponding image block and the second preset coefficient, that is, the distortion parameter size of the image block after the distortion parameter size reduction processing is:
  • the strategy adopted for the gradient of the distortion parameter size reduction of the image block is not limited to the product of the distortion parameter size of the corresponding image block and the second preset coefficient, and may be other.
  • each first image frame has the same strategy for reducing the size of the distortion parameter, so that the transition of the effect of distortion reduction in the same video frame is smoother.
  • the position of the image block for which the distortion parameter is reduced is the same.
  • the 1.0F distortion parameter size of each first image frame in the first video frame is reduced, and the 1.0F and 0.9F distortion parameter sizes of each first image frame in the second video frame are respectively performed. Reduce processing.
  • the second preset coefficients corresponding to the image blocks at the same position are the same, and the second preset coefficients corresponding to the image blocks at different positions are different, which is reduced by using different distortions.
  • the strategy reduces the distortion parameter sizes of image blocks at different positions in the first image frame to weaken the distortion difference between different positions in the first image frame, thereby weakening the sense of acceleration of the first image frame.
  • the second preset coefficients corresponding to image blocks at different positions in each image block whose distortion size is reduced are positively correlated with the distance from the image block to the image center, that is, from the image center The farther the image block corresponds to the larger the second preset coefficient, the more obvious the distortion stretching effect of the corresponding image block is, and the acceleration of the first image frame is weakened.
  • the difference between the second preset coefficients corresponding to two adjacent image blocks in each image block whose distortion size is reduced is a preset size, for example, for a certain
  • the second preset coefficient corresponding to 1.0F is 30%
  • the second preset coefficient corresponding to 0.9F is 25%, that is, the preset size is 5%. It is understandable that the preset size It can also be other numerical values.
  • the second preset coefficients corresponding to image blocks at different positions in each image block whose distortion size is reduced are positively correlated with the distance from the image block to the image center, and the same In an image frame, the difference between the second preset coefficients corresponding to the image blocks at two adjacent positions in each image block whose distortion size is reduced is a preset size.
  • the second preset coefficients corresponding to image blocks at different positions in each image block whose distortion size is reduced are positively correlated with the distance from the image block to the image center, but In the same first image frame, the difference between the second preset coefficients corresponding to the image blocks at two adjacent positions in each image block whose distortion size is reduced is not a fixed value.
  • the first image frame between different video frames has different distortion parameter size reduction strategies.
  • the distortion parameter size of the first image frame between different video frames is reduced.
  • the distortion difference of the first image frame between different video frames is small, thereby weakening the sense of acceleration between different video frames.
  • the number of image blocks whose distortion parameter size is reduced for the first image frame between different video frames increases in sequence with the shooting sequence of the video frame, for example, for the first image frame with continuous shooting sequence.
  • the shooting sequence of the first video frame is earlier than that of the second video frame, and the number of image blocks whose distortion parameters are reduced is 1 for the first image frame of the first video frame;
  • the number of image blocks whose distortion parameter size is reduced in the first image frame of the video frame is 2.
  • the image blocks whose distortion parameter size is reduced for the first image frame between different video frames increase along the direction close to the image center, such as a 1.0F distortion for each first image frame in the first video frame
  • the parameter size is reduced, and the 1.0F and 0.9F distortion parameter sizes of each first image frame in the second video frame are respectively reduced.
  • the number of image blocks in which the distortion parameter size of the first image frame between different video frames is reduced sequentially increases with the shooting sequence of the video frame, and other methods can be selected.
  • the second preset coefficient corresponding to the image block at the same position sequentially decreases with the shooting timing of the video frame. For example, for a first video frame and a second video frame with consecutive shooting timings, the shooting timing of the first video frame precedes the second video frame, and the second video frame corresponds to 1.0F of each first image frame in the first video frame.
  • the coefficient is set to 25%, and the second preset coefficient corresponding to 1.0F of each first image frame in the second video frame is 30%, so that the sense of acceleration between different video frames is reduced.
  • the distortion parameter of at least one image block in the first image frame may be adjusted based on a preset template.
  • the preset template includes the distortion parameter size after the distortion parameter of each image block is adjusted; optionally, the preset template may include information related to the gradient of the distortion parameter adjusted for each image block, as described in the above embodiment.
  • the information about the adjusted gradient may also be determined based on the distortion parameter of each image block in each first image.
  • the first preset parameter or second preset parameter of the corresponding image block can be determined according to the distortion parameter of each image block in the same first image frame, for example, the image block with larger distortion parameter can be distorted
  • the gradient of the parameter increase is also larger; or, for an image block with a larger distortion parameter, the gradient of the distortion parameter reduction is also larger.
  • the image processing method of the foregoing embodiment can be applied to an image processing device such as a computer that can perform image processing, and can also be applied to a photographing device.
  • applying the image processing method to the shooting device can simplify the shooting effect of the shooting device to achieve the expected sense of movement and reduce the cost of post-editing.
  • the camera of this embodiment can be mounted on mobile devices such as drones or bicycles.
  • the video file is a real-time video code stream acquired by the camera, and the camera performs distortion adjustment on the real-time video stream as needed to obtain video frames that meet the expected sense of motion.
  • the photographing device may include an image acquisition module and a processor, wherein the image acquisition module is used to photograph a video stream and store it in the buffer of the photographing device, and the processor of the photographing device obtains the real-time video stream from the buffer and analyzes the real-time video Make distortion adjustments.
  • the image acquisition module includes a lens and an imaging sensor matched with the lens, such as image sensors such as CCD and CMOS.
  • the camera entering the distortion adjustment program ie, the image processing method of the above-mentioned embodiment
  • the image processing method of this embodiment may further include: when it is determined that the photographing device satisfies the distortion adjustment strategy, controlling the photographing device to enter the distortion adjustment procedure.
  • the methods for the camera to determine whether it satisfies the distortion adjustment strategy may include but are not limited to the following:
  • a trigger signal is obtained, and the trigger signal is used to instruct the camera to perform distortion adjustment to enhance or weaken the sense of motion of the real-time video stream.
  • the trigger signal includes a first trigger signal, which is used to instruct the camera to enhance the sense of motion of the real-time video stream.
  • the first trigger signal After the camera obtains the first trigger signal, it will adopt the distortion adjustment strategy of the embodiment shown in FIG. 5A ( This article is also referred to as the first distortion adjustment strategy) to adjust the distortion of the real-time video stream;
  • the trigger signal includes a second trigger signal, which is used to instruct the camera to weaken the sense of motion of the real-time video stream.
  • the distortion adjustment strategy of the embodiment shown in FIG. 5B (also referred to as the second distortion adjustment strategy herein) is used to adjust the distortion of the real-time video stream.
  • the trigger signal can be generated based on different methods.
  • the trigger signal can be sent by an external device.
  • the external device can be a remote controller for controlling the drone, or with UAV communication terminal equipment, such as mobile phones, wearable devices, etc.
  • the trigger signal is triggered by the first control part of the camera, and the first control part may include keys, buttons or knobs.
  • the first control part includes two, one of the first control part will generate the first trigger signal after being triggered, and the other first control part will generate the second trigger signal after being triggered. At the same time, only Trigger one of the two first control sections.
  • the first control unit is electrically coupled to the processor of the imaging device, and the trigger signal generated by the first controller being triggered is transmitted to the processor of the imaging device, thereby triggering the processor of the imaging device to enter the distortion adjustment strategy.
  • the speed of the camera is acquired, and when the speed is greater than or equal to the preset speed threshold, it is determined that the camera meets the first distortion adjustment strategy. If the speed is less than the preset speed threshold, the acceleration of the camera can be further obtained. When the acceleration is greater than the preset acceleration threshold, it is determined that the camera meets the first distortion adjustment strategy. Of course, the speed and acceleration of the camera can also be obtained at the same time.
  • the first distortion adjustment strategy is used to instruct the camera to increase the distortion parameter size of at least one image block in the first image frame to generate the second image frame. For details, please refer to the corresponding part of the embodiment shown in FIG. 5A .
  • the speed and acceleration of the camera are acquired; when the speed is less than the preset speed threshold and the acceleration is less than or equal to the preset acceleration threshold, it is determined that the camera meets the second distortion adjustment strategy.
  • the second distortion adjustment strategy is used to instruct the camera to reduce the distortion parameter size of at least one image block in the first image frame to generate a second image frame.
  • the preset speed threshold and the preset acceleration threshold can be set as required.
  • the speed and acceleration are determined based on the detection data of the gyroscope on the camera and/or the real-time video stream captured by the camera.
  • the gyroscope can be set inside the lens center of the shooting device, and the lens center is mapped in the first image frame as the image center. In the first image frame, the distortion of the image center is the smallest. It is determined by detecting the speed and acceleration of the lens center The distortion adjustment strategy is more in line with the actual shooting scene.
  • the determination of the speed and acceleration based on the detection data of the gyroscope on the shooting device and/or the real-time video stream captured by the shooting device is the prior art, and will not be repeated here.
  • the stop signal is used to instruct the camera to stop the distortion adjustment program currently running.
  • the stop signal can also be generated in different ways.
  • the stop signal is sent by an external device.
  • the external device can be a remote control for controlling the drone, or Terminal devices that communicate with drones, such as mobile phones, wearable devices, etc.
  • the stop signal is triggered by the second control part of the camera, and the second control part may include keys, buttons or knobs.
  • the second control part and the first control part are the same component, and when the first control part is in a triggered state, a trigger signal is generated; when the first control part is switched from a triggered state to a non-triggered state, a stop signal is generated.
  • an embodiment of the present invention also provides an image processing device.
  • the image processing device 100 may include a storage device 110 and one or more processors 120.
  • the storage device 110 is used to store program instructions.
  • the one or more processors 120 call program instructions stored in the storage device, and when the program instructions are executed, the one or more processors 120 are individually or collectively configured to: Reading the first image frame in the video file; adjusting the distortion parameter of at least one image block in the first image frame to generate a second image frame; using the second image frame to replace the first image frame.
  • the processor 120 may implement the image processing method in the embodiment shown in FIG. 1 of the present invention, and the image processing apparatus in this embodiment can be described with reference to the image processing method in the foregoing embodiment.
  • the image processing device of this embodiment may be an image processing device, and the image processing device may be a device with image processing capabilities such as a computer; the image processing device may also be a photographing device with a camera function, such as a camera, Cameras, smart phones, smart terminals, shooting stabilizers, unmanned aerial vehicles, etc.
  • the processor may include the processor of the photographing device.
  • the photographing device may also include an image acquisition module (such as a camera).
  • the imaging device may also include a first control unit and/or a second control unit, and/or the imaging device can communicate with an external device.
  • the external device can be used to control the drone Remote control, or terminal equipment that communicates with the drone, such as mobile phones, wearable devices, etc.
  • an embodiment of the present invention also provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the steps of the image processing method of the foregoing embodiment are implemented. Specifically, when the program is executed by the processor, the following steps are implemented: read the first image frame in the video file; increase the distortion parameter of at least one image block in the first image frame to generate the second image frame; use The second image frame replaces the first image frame.
  • an embodiment of the present invention also provides a method for enhancing the sense of motion of an image.
  • the method may include the following steps:
  • S702 Increase the distortion parameter of the local area of the image frame in the video file
  • the local area may include at least one image block in each image frame of the video file, where the division method of the image block and the method of increasing the distortion parameter of the local area of the image frame in the video file can be referred to above
  • the description of the corresponding part of the image processing method of the embodiment will not be repeated here.
  • S703 Generate a new video file based on the adjusted video file.
  • the method for enhancing image motion in the embodiment shown in FIG. 7 can be applied to image processing equipment such as a computer, and can also be applied to a photographing device, which may be a camera with a photographing function, a video camera, a smart phone, or a smart terminal, Shooting stabilizers, unmanned aerial vehicles, etc.
  • a photographing device which may be a camera with a photographing function, a video camera, a smart phone, or a smart terminal, Shooting stabilizers, unmanned aerial vehicles, etc.
  • an embodiment of the present invention also provides a method for enhancing the sense of motion of an image.
  • the method may include the following steps:
  • S802 Increase a distortion parameter of at least one image block in the first image frame to generate a second image frame;
  • the method for enhancing image motion in the embodiment shown in FIG. 8 can be applied to image processing equipment such as a computer, and can also be applied to a photographing device, which may be a camera with a photographing function, a video camera, a smart phone, or a smart terminal, Shooting stabilizers, unmanned aerial vehicles, etc.
  • a photographing device which may be a camera with a photographing function, a video camera, a smart phone, or a smart terminal, Shooting stabilizers, unmanned aerial vehicles, etc.
  • the mobile terminal 200 includes: a photographing device 210, a storage device 220, and one or more The processor 230.
  • the shooting device 210 is used to obtain a video file;
  • the storage device 220 is used to store program instructions;
  • one or more processors 230 call the program instructions stored in the storage device, and when the program instructions are executed,
  • the one or more processors 230 are individually or collectively configured to: read the first image frame in the video file; increase the distortion parameter of at least one image block in the first image frame to generate A second image frame; using the second image frame to replace the first image frame.
  • the video file in this embodiment is a real-time video stream captured by the camera 210.
  • an embodiment of the present invention also provides an unmanned aerial vehicle.
  • the unmanned aerial vehicle 300 includes a fuselage 310 and is mounted on the fuselage.
  • the shooting device 320 is used to obtain a video file; the storage device 330 is used to store program instructions; one or more processors 340 call the program instructions stored in the storage device, and when the program instructions are executed,
  • the one or more processors 340 are individually or collectively configured to: read the first image frame in the video file; increase the distortion parameter of at least one image block in the first image frame to generate A second image frame; using the second image frame to replace the first image frame.
  • the video file in this embodiment is a real-time video stream captured by the camera 310.
  • the drone 300 in this embodiment of the present invention refers to an aerial photography drone, and other drones that do not have a camera function do not belong to the protection subject of this embodiment.
  • the UAV 300 may be a multi-rotor UAV or a fixed-wing UAV.
  • the embodiment of the present invention does not specifically limit the type of the UAV.
  • the camera 320 can be mounted on the fuselage 310 via a pan/tilt, and the camera 320 can be stabilized by the pan/tilt.
  • the pan/tilt can be a two-axis pan/tilt or a three-axis pan/tilt. The embodiment of the invention does not specifically limit this.
  • the handheld pan/tilt 400 includes: a photographing device 410, a storage device 420, and one or Multiple processors 430.
  • the shooting device 410 is used to obtain a video file;
  • the storage device 420 is used to store program instructions;
  • one or more processors 430 call the program instructions stored in the storage device, and when the program instructions are executed,
  • the one or more processors 430 are individually or collectively configured to: read the first image frame in the video file; increase the distortion parameter of at least one image block in the first image frame to generate A second image frame; using the second image frame to replace the first image frame.
  • the video file in this embodiment is a real-time video stream captured by the camera 410.
  • the handheld pan/tilt 400 in this embodiment of the present invention refers to a pan/tilt with a camera function, and other pan/tilts without a camera function do not belong to the protection subject of this embodiment.
  • the handheld gimbal 400 can be a two-axis gimbal or a three-axis gimbal to meet different stabilization requirements.
  • the photographing device 500 includes: an image acquisition module 510, a storage device 520, and one or more One processor 530.
  • the image acquisition module 510 is used to obtain video files;
  • the storage device 520 is used to store program instructions;
  • one or more processors 530 call the program instructions stored in the storage device, and when the program instructions are executed
  • the one or more processors 530 are individually or collectively configured to: read the first image frame in the video file; increase the distortion parameter of at least one image block in the first image frame to Generate a second image frame; use the second image frame to replace the first image frame.
  • the video file in this embodiment is a real-time video stream obtained by the image acquisition module 510.
  • the shooting device 500 can be a camera with a camera function, a video camera, a smart phone, a smart terminal, a shooting stabilizer (such as a handheld PTZ), an unmanned aerial vehicle (such as a drone), and so on.
  • the aforementioned storage device may include volatile memory, such as random-access memory (RAM); the storage device may also include non-volatile memory, such as flash memory ( flash memory, hard disk drive (HDD) or solid-state drive (SSD); the storage device 110 may also include a combination of the foregoing types of memory.
  • volatile memory such as random-access memory (RAM)
  • non-volatile memory such as flash memory ( flash memory, hard disk drive (HDD) or solid-state drive (SSD)
  • SSD solid-state drive
  • the storage device 110 may also include a combination of the foregoing types of memory.
  • the foregoing processor may be a central processing unit (CPU).
  • the processor may further include a hardware chip.
  • the aforementioned hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD) or a combination thereof.
  • ASIC application-specific integrated circuit
  • PLD programmable logic device
  • the above-mentioned PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL) or any combination thereof.
  • CPLD complex programmable logic device
  • FPGA field-programmable gate array
  • GAL generic array logic
  • the program can be stored in a computer readable storage medium. During execution, it may include the procedures of the above-mentioned method embodiments.
  • the storage medium may be a magnetic disk, an optical disc, a read-only memory (Read-Only Memory, ROM), or a random access memory (Random Access Memory, RAM), etc.

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Abstract

La présente invention concerne un procédé et un appareil de traitement d'image, le procédé consistant : à lire une première trame d'image dans un fichier vidéo ; à régler des paramètres de distorsion d'au moins un bloc d'image dans la première trame d'image pour générer une seconde trame d'image ; et à utiliser la seconde trame d'image pour remplacer la première trame d'image. Grâce au réglage des paramètres de distorsion d'un bloc d'image dans la première trame d'image dans le fichier vidéo, le présent procédé acquiert une seconde trame d'image ayant un meilleur effet visuel, et utilise la seconde trame d'image pour remplacer la première trame d'image, de telle sorte que l'effet de mouvement affiché par l'image lorsque le fichier vidéo est lu est mieux adapté aux exigences visuelles de l'œil humain, sans qu'il soit nécessaire de régler la vitesse de lecture vidéo.
PCT/CN2019/083920 2019-04-23 2019-04-23 Procédé et appareil de traitement d'image Ceased WO2020215214A1 (fr)

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CN107154027A (zh) * 2017-04-17 2017-09-12 深圳大学 一种畸变图像复原的补偿方法及装置

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CN114449237A (zh) * 2020-10-31 2022-05-06 华为技术有限公司 一种反畸变反色散的方法以及相关设备
CN114449237B (zh) * 2020-10-31 2023-09-29 华为技术有限公司 一种反畸变反色散的方法以及相关设备
CN116781844A (zh) * 2023-06-08 2023-09-19 深圳市火族科技有限公司 拉伸回弹视频转场特效的生成方法、系统及相关设备

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