WO2015196681A1 - 一种图片处理方法及电子设备 - Google Patents

一种图片处理方法及电子设备 Download PDF

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Publication number
WO2015196681A1
WO2015196681A1 PCT/CN2014/089902 CN2014089902W WO2015196681A1 WO 2015196681 A1 WO2015196681 A1 WO 2015196681A1 CN 2014089902 W CN2014089902 W CN 2014089902W WO 2015196681 A1 WO2015196681 A1 WO 2015196681A1
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WIPO (PCT)
Prior art keywords
picture
quality parameter
sharpness
exif information
weighting factor
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Ceased
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PCT/CN2014/089902
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English (en)
French (fr)
Inventor
晏国淇
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ZTE Corp
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ZTE Corp
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Priority to KR1020167035999A priority Critical patent/KR101867497B1/ko
Priority to US15/321,168 priority patent/US10212363B2/en
Priority to EP14896009.9A priority patent/EP3163865A4/en
Publication of WO2015196681A1 publication Critical patent/WO2015196681A1/zh
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
    • H04N5/76—Television signal recording
    • H04N5/765—Interface circuits between an apparatus for recording and another apparatus
    • H04N5/77—Interface circuits between an apparatus for recording and another apparatus between a recording apparatus and a television camera
    • H04N5/772—Interface circuits between an apparatus for recording and another apparatus between a recording apparatus and a television camera the recording apparatus and the television camera being placed in the same enclosure
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
    • H04N1/21—Intermediate information storage
    • H04N1/2104—Intermediate information storage for one or a few pictures
    • H04N1/2112—Intermediate information storage for one or a few pictures using still video cameras
    • H04N1/2125—Display of information relating to the still picture recording
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
    • H04N1/21—Intermediate information storage
    • H04N1/2166—Intermediate information storage for mass storage, e.g. in document filing systems
    • 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
    • H04N23/63—Control of cameras or camera modules by using electronic viewfinders
    • 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
    • H04N23/64—Computer-aided capture of images, e.g. transfer from script file into camera, check of taken image quality, advice or proposal for image composition or decision on when to take image
    • 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
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30168—Image quality inspection
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N2101/00—Still video cameras
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N2201/00—Indexing scheme relating to scanning, transmission or reproduction of documents or the like, and to details thereof
    • H04N2201/32—Circuits or arrangements for control or supervision between transmitter and receiver or between image input and image output device, e.g. between a still-image camera and its memory or between a still-image camera and a printer device
    • H04N2201/3201—Display, printing, storage or transmission of additional information, e.g. ID code, date and time or title
    • H04N2201/3212—Display, printing, storage or transmission of additional information, e.g. ID code, date and time or title of data relating to a job, e.g. communication, capture or filing of an image
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N2201/00—Indexing scheme relating to scanning, transmission or reproduction of documents or the like, and to details thereof
    • H04N2201/32—Circuits or arrangements for control or supervision between transmitter and receiver or between image input and image output device, e.g. between a still-image camera and its memory or between a still-image camera and a printer device
    • H04N2201/3201—Display, printing, storage or transmission of additional information, e.g. ID code, date and time or title
    • H04N2201/3225—Display, printing, storage or transmission of additional information, e.g. ID code, date and time or title of data relating to an image, a page or a document
    • H04N2201/3226—Display, printing, storage or transmission of additional information, e.g. ID code, date and time or title of data relating to an image, a page or a document of identification information or the like, e.g. ID code, index, title, part of an image, reduced-size image
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N2201/00—Indexing scheme relating to scanning, transmission or reproduction of documents or the like, and to details thereof
    • H04N2201/32—Circuits or arrangements for control or supervision between transmitter and receiver or between image input and image output device, e.g. between a still-image camera and its memory or between a still-image camera and a printer device
    • H04N2201/3201—Display, printing, storage or transmission of additional information, e.g. ID code, date and time or title
    • H04N2201/3225—Display, printing, storage or transmission of additional information, e.g. ID code, date and time or title of data relating to an image, a page or a document
    • H04N2201/3252—Image capture parameters, e.g. resolution, illumination conditions, orientation of the image capture device
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N2201/00—Indexing scheme relating to scanning, transmission or reproduction of documents or the like, and to details thereof
    • H04N2201/32—Circuits or arrangements for control or supervision between transmitter and receiver or between image input and image output device, e.g. between a still-image camera and its memory or between a still-image camera and a printer device
    • H04N2201/3201—Display, printing, storage or transmission of additional information, e.g. ID code, date and time or title
    • H04N2201/3274—Storage or retrieval of prestored additional information
    • H04N2201/3277—The additional information being stored in the same storage device as the image data

Definitions

  • the present invention relates to image processing technologies in the field of communications, and in particular, to a picture processing method and an electronic device.
  • Google’s native Camera Gallery provides an experience to categorize photos based on time and place. But in fact, the browsing experience that is categorized from time and place alone does not meet the needs of users. On the other hand, since most people who use mobile phones are not professionals, limited by the shooting skills and the tempo of shooting, there is no guarantee that the quality of each photo will be the best. For example, in a moving scene, it is easy to take a blurred photo because the focus is not on. When taking pictures outdoors, it is easy to take over-exposed and noisy pictures because of the weather and light. Users generally want to browse the best photos they have taken when browsing photos. In addition, after the user takes a photo, they will check whether the photo is satisfactory, then adjust the scene to take the next photo. In some cases, after the user takes a group of photos in succession, they can view them one by one, and then delete the photos that are not satisfactory. Usually browsing a group of similar photos one by one takes a certain amount of time and effort.
  • an object of the embodiments of the present invention is to provide a picture processing method and an electronic device.
  • An embodiment of the present invention provides a picture processing method, where the method includes:
  • the quality parameter corresponding to the picture is calculated by using the sharpness average value and the number of noises, and the picture is stored or displayed according to the quality parameter.
  • the method further includes: acquiring a specified focus coordinate; or setting a center coordinate of the picture as a focus coordinate.
  • the calculating the quality parameter corresponding to the picture by using the sharpness average value and the number of noises including:
  • the determining the corresponding weighting factor according to the extended EXIF information includes: extracting a flash parameter in the extended EXIF, and when the flash is not turned on according to the flash parameter, the weighting factor is the first group. Weighting factor; otherwise, the weighting factor is a second set of weighting factors.
  • the method further includes: classifying the picture according to the quality parameter, to obtain a level corresponding to the picture;
  • the storing the image according to the quality parameter is:
  • the parameter is stored in the database by using the identifier of the image as an index; or the quality parameter and the level of the image are stored in the database by using the identifier of the image as an index;
  • the displaying the image according to the quality parameter is: when displaying a picture, displaying the picture according to a quality parameter or a level of the picture.
  • An embodiment of the present invention provides an electronic device, where the electronic device includes:
  • a processing unit when acquiring a picture, adding focus coordinates corresponding to the picture to the EXIF information corresponding to the picture, to obtain extended EXIF information; determining a body area of the picture according to the extended EXIF information; The quality parameter stores or displays the picture.
  • a calculating unit configured to calculate a sharpness average value corresponding to the body region, and detect a number of noises of the body region; using the sharpness average value and the number of noises, calculating a quality corresponding to the image parameter.
  • the processing unit is further configured to acquire a specified focus coordinate; or set a center coordinate of the picture as a focus coordinate.
  • the calculating unit is specifically configured to convert the sharpness average value into a sharpness score value, convert the noise number into a noise score value, and determine a corresponding weight according to the extended EXIF information. And using the weighting factor, the sharpness score value, and the noise score value to calculate a quality parameter corresponding to the picture.
  • the calculating unit is further configured to extract a flash parameter in the extended EXIF, and when the flash is not turned on according to the flash parameter, the weighting factor is a first group weighting factor; otherwise, the weight is The factor is the second set of weighting factors.
  • the calculating unit is further configured to classify the picture according to the quality parameter, to obtain a level corresponding to the picture;
  • the processing unit is configured to store the quality parameter as an index into a database by using an identifier of the image; or, storing the quality parameter and the level of the image as an index of the image to a database; And when displaying the picture, according to the quality parameter, or the picture The level of the slice shows the picture.
  • the image processing method and the electronic device provided by the embodiments of the present invention record the focus coordinates of the image in the EXIF information by expanding the EXIF information; and cutting the main body region by reading the focus coordinates;
  • the sharpness and the number of noises determine the quality parameters corresponding to the picture, and can also be stored and displayed according to the quality parameters. It can be seen that the solution provided by the present invention can quickly determine the picture quality, thereby helping the user to optimize and filter the picture, which is convenient for the user to view.
  • FIG. 1 is a schematic flowchart of a picture processing method according to an embodiment of the present invention.
  • FIG. 2 is a schematic view showing the position of a main body area according to an embodiment of the present invention.
  • FIG. 3 is a second schematic diagram of a position of a main body area according to an embodiment of the present invention.
  • FIG. 4 is a schematic diagram of determining a picture sharpness value according to an embodiment of the present invention.
  • FIG. 5 is a schematic diagram of detecting noise according to an embodiment of the present invention.
  • FIG. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
  • the image processing method provided by the embodiment of the present invention, as shown in FIG. 1 includes:
  • Step 101 When collecting a picture, add focus coordinates corresponding to the picture to the EXIF (Exchangeable Image File) information corresponding to the picture, to obtain extended EXIF information.
  • EXIF Exchangeable Image File
  • Step 102 Determine a body area of the picture according to the extended EXIF information.
  • Step 103 Calculate an average value of sharpness corresponding to the body region, and detect the number of noises of the body region.
  • Step 104 Calculate a quality parameter corresponding to the picture by using the sharpness average value and the number of noises, and store or display the picture according to the quality parameter.
  • the captured picture may be a picture taken by a user through a camera provided on the electronic device
  • the electronic device may be a smart phone, a tablet computer, or a digital camera.
  • Adding the focus coordinate corresponding to the picture to the EXIF information corresponding to the picture may include: adding a focus coordinate corresponding to the picture to the EXIF information by modifying a Camera code of the HAL layer.
  • the default EXIF information includes: the time, size, and whether the flash is turned on.
  • the method for acquiring the focus coordinates may include: acquiring a focus coordinate specified by the user; or setting a center coordinate of the picture as a focus coordinate.
  • the focus coordinates specified by the user may be detected by detecting the operation of the user. For example, when taking a picture using a smartphone, the user may specify the focus coordinates by touching the screen.
  • Determining, according to the extended EXIF information, the body area of the picture may include: when the distance of the focus coordinate from the four sides of the picture is not less than a preset distance value, using the focus coordinate as a center point, The rectangle with the specified length and width values is taken as the main area; for example, as shown in FIG. 2, the original picture width is W, the height is H, the focus coordinate 21 is the center point P, and the P is the center point, and the intercepted body area is specified.
  • the rectangle with the specified length and width value as the center point with the focus coordinate as the center point the first area
  • An area in which an area coincides with the picture is used as a main area; for example, as shown in FIG. 3, the focus coordinate is close to a corner of the picture, and then the focus 31 is first taken as a center point, and the rectangle of the specified length and width value is determined as the first area 321 That is, the area shown by the dotted line in FIG.
  • a region in which the first region 321 coincides with the original image, that is, a rectangular region having a darker color in FIG. 3 is determined as the body region 322.
  • the calculating the sharpness average value corresponding to the body region may include: calculating an edge value corresponding to four sides and two diagonal lines of the body region by using an edge sharpness algorithm, and calculating an average value of sharpness .
  • an edge value corresponding to four sides and two diagonal lines of the body region As shown in FIG. 4, specifically, four sides and two diagonal lines of the main body area are selected; and gray scale change values of the image on the four sides and two diagonal lines are respectively calculated, and the gray level change value is used as The sharpness value, the sharper the gray scale change, the clearer the image, and then the sharpness values of the four sides and the two diagonal lines are averaged as the sharpness value of the body region.
  • Sharpness the sharpness of a picture, is an important indicator of image clarity.
  • d f /d x is the rate of change of gray in the edge direction
  • f(b)-f(a) is the overall change in the direction
  • a and b respectively represent the two endpoints of the currently calculated line, such as If a diagonal is calculated, a and b are the two endpoints of the diagonal, respectively.
  • Picture noise means that the pixel value of a point is very different from the surrounding, and it is also a factor to measure the picture quality. Referring to Figure 5, the more the number of noises, the less the score. If the pixel point A is different from the surrounding 8 pixel values, it is determined as noise, and the detection of the edge point is ignored in the noise detection.
  • L p (c) represents the sum of the noise vectors
  • c represents the 8 neighborhoods around the center point A
  • x o (c) represents the gray value of the central pixel point
  • x k (c) represents the vicinity of the center point A.
  • Domain pixel, N 8. If L p (c) is greater than the preset decision threshold, it is determined that the center point is noise. The less the number of picture noises, the more beautiful the picture and the higher the quality.
  • Calculating, by using the sharpness average value and the number of noises, the quality parameter corresponding to the picture may include: converting the sharpness average value into a sharpness score value, and using the noise level The number is converted into a noise score value, and a corresponding weighting factor is determined according to the extended EXIF information, and the quality parameter corresponding to the picture is calculated by using the weighting factor, the sharpness score value, and the noise score value.
  • the sharpness score is S1
  • the noise score is S2
  • the corresponding weight factor sharpness score value corresponds to a
  • the noise score value corresponds to b
  • the converting the sharpness average value into the sharpness score value may be: after a large number of image simulations, if the sharpness value is determined to be 5 points in the interval [1100, 1200], the interval [1000, 1100] is determined as 4 points, the interval [900, 1000] was judged to be 3 points, the interval [700, 900] was judged to be 2 points, and the sharpness was determined to be 1 point when the sharpness was lower than 700.
  • the converting the number of noises into a noise score value may include: if the number of noises in the body region is [0, 10] is determined to be 5 points, [11, 20] is determined to be 4 points, [21, 35] determining It is 3 points, [36, 45] is judged to be 2, and the number of noises exceeding 45 is judged to be 1 point.
  • TAG_FLASH flash parameter
  • the method further includes: classifying the picture according to the quality parameter, and obtaining a level corresponding to the picture, for example, determining that the quality parameter score interval is [4.5, 5] is excellent, and determining the interval [3.5, 4.4] For good, [2.5, 3.4] is judged to be general, and [1, 2.4] is judged to be poor.
  • the storing the image according to the quality parameter may be: storing the quality parameter as an index of a picture to a database; or storing the quality parameter and a level of the picture to a database; wherein
  • the identifier of the picture may be the name of the picture, or the shooting time of the picture, and the like.
  • Displaying the picture according to the quality parameter may be: when the picture is displayed, the picture is displayed according to a quality parameter or a level of the picture. For example, when the user needs to view the picture by opening the gallery, the result can be classified according to the quality parameter according to the needs, and all the pictures in the database are hierarchically displayed to the user for browsing.
  • the user may also perform filtering, deleting, and the like according to the level of the picture when displaying the picture.
  • the electronic device provided by the embodiment of the present invention, as shown in FIG. 6, includes:
  • the processing unit 61 is configured to: add focus coordinates corresponding to the picture to the EXIF (Exchangeable Image File) information corresponding to the picture to obtain extended EXIF information; and obtain extended EXIF information according to the extended EXIF information. Determining a body area of the picture;
  • a calculation unit 62 configured to calculate a sharpness average value corresponding to the body region, and detect a number of noises of the body region; and use the sharpness average value and the number of noises to calculate a corresponding image a quality parameter, the picture is stored or displayed according to the quality parameter.
  • the electronic device may be a smartphone, or a tablet computer, or a digital camera or the like.
  • the processing unit 61 is specifically configured to add the focus coordinates corresponding to the picture to the EXIF information by modifying the Camera code of the HAL layer.
  • the default EXIF information includes: the time, size, and whether the flash is turned on.
  • the processing unit 61 is further configured to acquire a focus coordinate specified by the user, or set a center coordinate of the picture as a focus coordinate.
  • the processing unit 61 is further configured to: when the distance of the focus coordinate from the four sides of the picture is not less than a preset distance value, using the focus coordinate as a center point, and the focus coordinate as a center point,
  • the rectangle with the specified length and width values is used as the main area; for example, as shown in Figure 2, the original picture is recorded.
  • the width is W
  • the height is H
  • the focus coordinate 21 is the center point P
  • P the center point
  • the rectangle with the specified length and width value is taken as the first area with the focus coordinate as the center point, and the The area where the first area coincides with the picture is used as the main area; for example, as shown in FIG. 3, the focus coordinate is close to a corner of the picture, and then the focus 31 is used as the center point, and the rectangle of the specified length and width value is determined as the first
  • the area 321 is the area shown by the dotted line in FIG.
  • the area where the first area 321 coincides with the original picture, that is, the rectangular area of the darker color in FIG. 3 is taken as the main body area 322.
  • the calculating unit 62 is further configured to calculate, by using an edge sharpness algorithm, a sharpness value corresponding to each of the four sides of the body region and the two diagonal lines, and calculate an average value of the sharpness.
  • an edge sharpness algorithm calculates, by using an edge sharpness algorithm, a sharpness value corresponding to each of the four sides of the body region and the two diagonal lines, and calculate an average value of the sharpness.
  • FIG. 4 specifically, four sides and two diagonal lines of the main body area are selected; and gray scale change values of the image on the four sides and two diagonal lines are respectively calculated, and the gray level change value is used as The sharpness value, the sharper the gray scale change, the clearer the image, and then the sharpness values of the four sides and the two diagonal lines are averaged as the sharpness value of the body region.
  • Sharpness the sharpness of a picture, is an important indicator of image clarity.
  • d f /d x is the rate of change of gray in the edge direction
  • f(b)-f(a) is the overall change in the direction
  • a and b respectively represent the two endpoints of the currently calculated line, such as If a diagonal is calculated, a and b are the two endpoints of the diagonal, respectively.
  • Picture noise means that the pixel value of a point is very different from the surrounding, and it is also a factor to measure the picture quality. Referring to Figure 5, the more the number of noises, the less the score. If the pixel point A is different from the surrounding 8 pixel values, it is determined as noise, and the detection of the edge point is ignored in the noise detection.
  • L p (c) represents the sum of the noise vectors
  • c represents the 8 neighborhoods around the center point A
  • x o (c) represents the gray value of the central pixel point
  • x k (c) represents the vicinity of the center point A.
  • Domain pixel, N 8. If L p (c) is greater than the preset decision threshold, it is determined that the center point is noise. The less the number of picture noises, the more beautiful the picture and the higher the quality.
  • the calculating unit 62 is further configured to convert the sharpness average value into a sharpness score value, convert the noise number into a noise score value, determine a corresponding weighting factor according to the extended EXIF information, and utilize The weighting factor, the sharpness score value, and the noise score value are calculated, and the quality parameter corresponding to the picture is calculated.
  • the sharpness score is S1
  • the noise score is S2
  • the corresponding weight factor sharpness score value corresponds to a
  • the noise score value corresponds to b
  • the converting the sharpness average value into the sharpness score value may be: after a large number of picture simulations, if the sharpness value is determined to be 5 points in the [1100, 1200] interval, the interval [1000, 1100] is determined as 4 points, the interval [900, 1000] was judged to be 3 points, the interval [700, 900] was judged to be 2 points, and the sharpness was determined to be 1 point when the sharpness was lower than 700.
  • the calculation unit 62 is further configured to determine that the number of noises in the body region is [0, 10] is 5 points, [11, 20] is determined to be 4 points, and [21, 35] is determined to be 3 points, [36, 45] The judgment is 2, and the number of noises exceeds 45 and is judged to be 1 point.
  • TAG_FLASH flash parameter
  • the calculating unit 62 is further configured to classify the picture according to the quality parameter to obtain a level corresponding to the picture, for example, determining that the quality parameter score interval is [4.5, 5] is excellent, and the interval is [3.5, 4.4] is judged to be good, [2.5, 3.4] is judged to be general, and [1, 2.4] is judged to be poor.
  • the calculating unit 62 is further configured to: categorize the image according to the quality parameter, to obtain a level corresponding to the picture; correspondingly, the processing unit is specifically configured to use the identifier of the quality parameter as a picture
  • the index is stored in the database; or the quality parameter and the level of the picture are stored in the database by using the identifier of the picture; and when the picture is displayed, the picture is performed according to the quality parameter or the level of the picture. Show.
  • the storing the image according to the quality parameter may be: storing the quality parameter as an index of a picture to a database; or storing the quality parameter and a level of the picture to a database; wherein
  • the identifier of the picture may be the name of the picture, or the shooting time of the picture, and the like.
  • Displaying the picture according to the quality parameter may be: when the picture is displayed, the picture is displayed according to a quality parameter or a level of the picture. For example, when the user needs to view the picture by opening the gallery, the result can be classified according to the quality parameter according to the needs, and all the pictures in the database are hierarchically displayed to the user for browsing. Further, the user may also perform filtering, deleting, and the like according to the level of the picture when displaying the picture.
  • the disclosed apparatus and method may be implemented in other manners.
  • the device embodiments described above are merely illustrative.
  • the division of the unit is only a logical function division.
  • there may be another division manner such as: multiple units or components may be combined, or Can be integrated into another system, or some features can be ignored or not executed.
  • the coupling, or direct coupling, or communication connection of the components shown or discussed may be indirect coupling or communication connection through some interfaces, devices or units, and may be electrical, mechanical or other forms. of.
  • the units described above as separate components may or may not be physically separated, and the components displayed as the unit may or may not be physical units, that is, may be located in one place or distributed to multiple network units; Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.
  • each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated into one unit;
  • the unit can be implemented in the form of hardware or in the form of hardware plus software functional units.
  • the foregoing program may be stored in a computer readable storage medium, and the program is executed when executed.
  • the foregoing storage device includes the following steps: the foregoing storage medium includes: a mobile storage device, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.
  • ROM read-only memory
  • RAM random access memory
  • magnetic disk or an optical disk.
  • optical disk A medium that can store program code.
  • the above-described integrated unit of the present invention may be stored in a computer readable storage medium if it is implemented in the form of a software function module and sold or used as a standalone product.
  • the technical solution of the embodiments of the present invention may be embodied in the form of a software product in essence or in the form of a software product stored in a storage medium, including a plurality of instructions.
  • a computer device (which may be a personal computer, server, or network device, etc.) is caused to perform all or part of the methods described in various embodiments of the present invention.
  • the foregoing storage medium includes: a removable storage device, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and the like, which can store program codes.
  • the invention discloses a picture processing method and an electronic device.
  • the focus coordinates of the picture are recorded in the EXIF information; by reading the focus coordinates, the picture body area is cut out as a center; then the body area is calculated.
  • the sharpness and the number of noises determine the quality parameters corresponding to the picture, and can also be stored and displayed according to the quality parameters. It can be seen that the solution provided by the present invention can quickly determine the picture quality, thereby helping the user to optimize and filter the picture, which is convenient for the user to view.

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Abstract

本发明公开了一种图片处理方法及电子设备，其中方法包括：采集图片时，将所述图片对应的焦点坐标添加到所述图片对应的可交换图像文件(EXIF)信息中，得到扩展EXIF信息；根据所述扩展EXIF信息确定所述图片的主体区域；计算所述主体区域对应的锐度平均值、并检测所述主体区域的噪点个数；利用所述锐度平均值以及所述噪点个数，计算得到所述图片对应的质量参数，根据所述质量参数对所述图片进行存储或展示。

Description

一种图片处理方法及电子设备 技术领域
本发明涉及通信领域的图像处理技术，尤其涉及一种图片处理方法及电子设备。
背景技术
随着智能手机的日益发展，摄像头Camera的性能和体验都得到很大提升。近年来智能终端大量普及，及Camera拍照的便捷性，使越来越多的用户习惯使用手机Camera来拍摄生活中照片，即时记录生活中一些场景。在使用过程中，随着时间的增加，用户往往拍摄了上百张甚至上千张照片。如何让用户在海量照片中快速选择出自己想要浏览的照片成为一个需要关注的问题。
Google原生的Camera图库提供了根据时间和地点对照片进行分类的体验。但实际上，单从时间和地点分类的浏览体验并不能满足用户的需求。另一方面，由于大多数用手机拍照者都不是专业人士，受限于拍摄技巧和拍摄的随时性，并不能保证每张照片质量都是最佳的。比如在移动场景中，很容易因对焦未对上拍出模糊的照片。在室外拍照时，因为天气和光线的原因很容易拍摄出过曝、有噪点的图片。用户在浏览照片一般都希望最先浏览自己拍摄的较好的照片。另外，用户拍摄完一张照片后都会查看照片是否满意，然后调整场景拍摄下一张照片。个别情况下，用户连续拍摄一组照片后，通过逐个筛选查看，然后删除其中不满意的照片。通常逐张浏览一组相近的照片会耗费用户一定的时间和精力。
发明内容
为解决上述技术问题，本发明实施例的目的在于提供一种图片处理方法及电子设备。
本发明实施例提供了一种图片处理方法，所述方法包括：
采集图片时，将所述图片对应的焦点坐标添加到所述图片对应的可交换图像文件EXIF信息中，得到扩展EXIF信息；
根据所述扩展EXIF信息确定所述图片的主体区域；
计算所述主体区域对应的锐度平均值、并检测所述主体区域的噪点个数；
利用所述锐度平均值以及所述噪点个数，计算得到所述图片对应的质量参数，根据所述质量参数对所述图片进行存储或展示。
上述方案中，所述方法还包括：获取指定的焦点坐标；或者设置所述图片的中心坐标为焦点坐标。
上述方案中，所述利用所述锐度平均值以及所述噪点个数，计算得到所述图片对应的质量参数，包括：
将所述锐度平均值转换为锐度得分值，将所述噪点个数转换为噪点得分值，根据所述扩展EXIF信息确定对应的权重因子，利用所述权重因子、锐度得分值、噪点得分值，计算得到所述图片对应的质量参数。
上述方案中，所述根据所述扩展EXIF信息确定对应的权重因子，包括：提取所述扩展EXIF中的闪光灯参数，当根据所述闪光灯参数确定没开启闪光灯时，所述权重因子为第一组权重因子；否则，所述权重因子为第二组权重因子。
上述方案中，所述方法还包括：根据所述质量参数对所述图片进行分级，得到所述图片对应的级别；
相应的，所述根据所述质量参数对所述图片进行存储为：将所述质量 参数以图片的标识为索引存储至数据库；或者，将所述质量参数和所述图片的级别，以图片的标识为索引存储至数据库；
所述根据所述质量参数对所述图片进行展示为：当展示图片时，按照质量参数、或者所述图片的级别将所述图片进行展示。
本发明实施例提供了一种电子设备，所述电子设备包括：
处理单元，用于采集图片时，将所述图片对应的焦点坐标添加到所述图片对应的EXIF信息中，得到扩展EXIF信息；根据所述扩展EXIF信息确定所述图片的主体区域；根据所述质量参数对所述图片进行存储或展示。
计算单元，用于计算所述主体区域对应的锐度平均值、并检测所述主体区域的噪点个数；利用所述锐度平均值以及所述噪点个数，计算得到所述图片对应的质量参数。
上述方案中，所述处理单元，还用于获取指定的焦点坐标；或者设置所述图片的中心坐标为焦点坐标。
上述方案中，所述计算单元，具体用于将所述锐度平均值转换为锐度得分值，将所述噪点个数转换为噪点得分值，根据所述扩展EXIF信息确定对应的权重因子，利用所述权重因子、锐度得分值、噪点得分值，计算得到所述图片对应的质量参数。
上述方案中，所述计算单元，还用于提取所述扩展EXIF中的闪光灯参数，当根据所述闪光灯参数确定没开启闪光灯时，所述权重因子为第一组权重因子；否则，所述权重因子为第二组权重因子。
上述方案中，所述计算单元，还用于根据所述质量参数对所述图片进行分级，得到所述图片对应的级别；
相应的，所述处理单元，具体用于将所述质量参数以图片的标识为索引存储至数据库；或者，将所述质量参数和所述图片的级别，以图片的标识为索引存储至数据库；以及当展示图片时，按照质量参数、或者所述图 片的级别将所述图片进行展示。
本发明实施例所提供的图片处理方法及电子设备，通过扩展EXIF信息，在EXIF信息里记录图片的焦点坐标；通过读取对焦点坐标，以此为中心切割出图片主体区域；然后计算主体区域的锐度和噪点个数，进而确定图片对应的质量参数，还可以根据质量参数进行存储以及展示。可见，采用本发明提供的方案能够快速的确定图片质量，进而帮助用户进行图片的优选、筛选，方便用户查看。
附图说明
图1为本发明实施例图片处理方法流程示意图；
图2为本发明实施例主体区域位置示意图一；
图3为本发明实施例主体区域位置示意图二；
图4为本发明实施例确定图片锐度值的示意图；
图5为本发明实施例检测噪点的示意图；
图6为本发明实施例电子设备组成结构示意图。
具体实施方式
下面结合附图及具体实施例对本发明再作进一步详细的说明。
实施例一、
本发明实施例提供的图片处理方法，如图1所示，包括：
步骤101：采集图片时，将所述图片对应的焦点坐标添加到所述图片对应的可交换图像文件(EXIF，Exchangeable Image File)信息中，得到扩展EXIF信息。
步骤102：根据所述扩展EXIF信息确定所述图片的主体区域。
步骤103：计算所述主体区域对应的锐度平均值、并检测所述主体区域的噪点个数。
步骤104：利用所述锐度平均值以及所述噪点个数，计算得到所述图片对应的质量参数，根据所述质量参数对所述图片进行存储或展示。
这里，所述采集图片可以为用户通过电子设备上具备的摄像头拍摄图片，所述电子设备可以为智能手机、或者平板电脑、或者数码相机等。
所述将所述图片对应的焦点坐标添加到所述图片对应的EXIF信息中可以包括：通过修改HAL层的Camera代码，将所述图片对应的焦点坐标添加到EXIF信息中。
默认的所述EXIF信息中包括：图片的采集时间、大小、是否开启闪光灯等信息。
所述焦点坐标的获取方法可以包括：获取用户指定的焦点坐标；或者设置所述图片的中心坐标为焦点坐标。其中，所述用户指定的焦点坐标可以检测用户的操作来确定，比如当使用智能手机拍照时，用户可以通过触摸屏幕来指定焦点坐标。
所述根据所述扩展EXIF信息确定所述图片的主体区域可以包括：当所述焦点坐标距离所述图片的四条边的距离均不小于预设距离值时，以所述焦点坐标为中心点、以指定长宽值的矩形为主体区域；比如，图2所示，记原始图片宽为W，高为H，对焦点坐标21为中心点P；以P为中心点，截取的主体区域指定宽度值为W1＝1/3*W，指定长度值为H1＝1/3*H的矩形；
当所述焦点坐标距离所述图片的四条边中任意一条边的距离小于预设距离值时，以所述焦点坐标为中心点、以指定长宽值的矩形作为第一区域，将所述第一区域与所述图片重合的区域作为主体区域；比如，图3所示，焦点坐标接近图片的一角，则首先将所述焦点31作为中心点，确定指定长宽值的矩形为第一区域321，即图3中虚线框中所示区域，所述第一区域指定宽度值可以为W1＝1/3*W，指定长度值可以为H1＝1/3*H的矩形；再 确定所述第一区域321与原始图片的重合的区域，即图3中颜色较深的矩形区域作为主体区域322。
优选地，所述计算所述主体区域对应的锐度平均值可以包括：利用边缘锐度算法计算所述主体区域四条边以及两条对角线分别对应的锐度值，计算得到锐度平均值。如图4所示，具体的，选取主体区域的四条边及两条对角线进行；分别计算图像在所述四条边及两条对角线上灰度变化值，所述灰度变化值作为所述锐度值，灰度变化越剧烈则图像越清晰，然后平均所述四条边及两条对角线上的锐度值作为主体区域的锐度值。锐度即图片的锐利程度，是衡量图像清晰度的重要指标。
计算图像在所述四条边及两条对角线上灰度变化值的计算公式如下：
Figure PCTCN2014089902-appb-000001
其中，df/dx为边缘方向上的灰度变化率，f(b)-f(a)为该方向上的总体变化，其中a和b分别代表当前计算的线的两个端点，比如，如果计算一条对角线时，a和b就分别为对角线的两个端点。
图片噪点是指某点的像素值跟周围差别很大，也是衡量图片质量的一个因素。参见图5，噪点个数越多得分越少。如果像素点A点，与周围8临域像素值差别很大则判定为噪点，噪点检测时忽略边缘点的检测。
所述检测噪点个数的公式如下：
Figure PCTCN2014089902-appb-000002
其中，Lp(c)表示噪点向量和，c表示中心点A周围的8临域区域；xo(c)表示中心像素点的灰度值，xk(c)表示中心点A周围的临域像素点，N＝8。如果Lp(c)大于预设的判定阈值则判定此中心点为噪点。一个图片噪点个数越少，表示图片越美观，质量越高。
所述利用所述锐度平均值以及所述噪点个数，计算得到所述图片对应的质量参数可以包括：将所述锐度平均值转换为锐度得分值，将所述噪点 个数转换为噪点得分值，根据所述扩展EXIF信息确定对应的权重因子，利用所述权重因子、锐度得分值、噪点得分值，计算得到所述图片对应的质量参数。比如，锐度得分为S1，噪点得分为S2，对应的权重因子锐度得分值对应为a和噪点得分值对应b，图片最终得分记为S＝a*S1+b*S2。
其中，所述将所述锐度平均值转换为锐度得分值可以为：经过大量图片仿真，如果锐度值在区间[1100,1200]判定为5分，区间[1000,1100]判定为4分，区间[900，1000]判定为3分，区间[700,900]判定为2分，锐度低于700判定为1分。
所述将所述噪点个数转换为噪点得分值可以包括：如果主体区域噪点个数为[0,10]判定为5分，[11,20]判定为4分，[21,35]判定为3分，[36,45]判定为2，噪点个数超过45判定为1分。
其中，所述根据所述扩展EXIF信息确定对应的权重因子可以包括：提取所述扩展EXIF中的闪光灯参数(TAG_FLASH)，当根据所述闪光灯参数确定没开启闪光灯时，所述权重因子为第一组权重因子；否则，所述权重因子为第二组权重因子；比如，如果为0则没有开启闪光灯，1为开启闪光灯；如果未开启闪光灯，则确定第一组权重因子为a＝0.6、b＝0.4；如果开启闪光灯，相较与正常情况，照片更容易出现噪点问题，则第二组权重因子为a＝0.4、b＝0.6。
优选地，还可以包括根据所述质量参数对所述图片进行分级，得到所述图片对应的级别，比如，将质量参数得分区间为[4.5,5]判定为优秀，区间[3.5,4.4]判定为良好，[2.5,3.4]判定为一般，[1,2.4]判定为差。
根据所述质量参数对所述图片进行存储可以为：将所述质量参数以图片的标识为索引存储至数据库；或者，将所述质量参数和所述图片的级别存储至数据库；其中，所述图片的标识可以为所述图片的名称、或者所述图片的拍摄时间等。
根据所述质量参数对所述图片进行展示可以为：当展示图片时，按照质量参数、或者所述图片的级别将所述图片进行展示。如，用户打开图库需要浏览图片时，可以根据需要按照质量参数进行分级得到的结果，将数据库中的全部图片进行分级展示给用户浏览。
进一步的，用户还可以在对图片进行展示时，根据所述图片的级别，对图片进行筛选、删除等操作。
实施例二、
本发明实施例提供的电子设备，如图6所示，包括：
处理单元61，用于采集图片时，将所述图片对应的焦点坐标添加到所述图片对应的可交换图像文件(EXIF，Exchangeable Image File)信息中，得到扩展EXIF信息；根据所述扩展EXIF信息确定所述图片的主体区域；
计算单元62，用于计算所述主体区域对应的锐度平均值、并检测所述主体区域的噪点个数；利用所述锐度平均值以及所述噪点个数，计算得到所述图片对应的质量参数，根据所述质量参数对所述图片进行存储或展示。
这里，所述电子设备可以为智能手机、或者平板电脑、或者数码相机等。
所述处理单元61，具体用于通过修改HAL层的Camera代码，将所述图片对应的焦点坐标添加到EXIF信息中。
默认的所述EXIF信息中包括：图片的采集时间、大小、是否开启闪光灯等信息。
所述处理单元61，还用于获取用户指定的焦点坐标；或者设置所述图片的中心坐标为焦点坐标。
所述处理单元61，还用于当所述焦点坐标距离所述图片的四条边的距离均不小于预设距离值时，以所述焦点坐标为中心点、以所述焦点坐标为中心点、以指定长宽值的矩形为主体区域；比如，图2所示，记原始图片 宽为W，高为H，对焦点坐标21为中心点P；以P为中心点，截取的主体区域指定宽度值为W1＝1/3*W，指定长度值为H1＝1/3*H的矩形；
当所述焦点坐标距离所述图片的四条边中任意一条边的距离小于预设距离值时，时，以所述焦点坐标为中心点、以指定长宽值的矩形作为第一区域，将所述第一区域与所述图片重合的区域作为主体区域；比如，图3所示，焦点坐标接近图片的一角，则首先将所述焦点31作为中心点，确定指定长宽值的矩形为第一区域321，即图3中虚线框中所示区域，所述第一区域指定宽度值可以为W1＝1/3*W，指定长度值可以为H1＝1/3*H的矩形；再确定所述第一区域321与原始图片的重合的区域，即图3中颜色较深的矩形区域作为主体区域322。
优选地，所述计算单元62，还用于利用边缘锐度算法计算所述主体区域四条边以及两条对角线分别对应的锐度值，计算得到锐度平均值。如图4所示，具体的，选取主体区域的四条边及两条对角线进行；分别计算图像在所述四条边及两条对角线上灰度变化值，所述灰度变化值作为所述锐度值，灰度变化越剧烈则图像越清晰，然后平均所述四条边及两条对角线上的锐度值作为主体区域的锐度值。锐度即图片的锐利程度，是衡量图像清晰度的重要指标。
计算图像在所述四条边及两条对角线上灰度变化值的计算公式如下：
Figure PCTCN2014089902-appb-000003
其中，df/dx为边缘方向上的灰度变化率，f(b)-f(a)为该方向上的总体变化，其中a和b分别代表当前计算的线的两个端点，比如，如果计算一条对角线时，a和b就分别为对角线的两个端点。
图片噪点是指某点的像素值跟周围差别很大，也是衡量图片质量的一个因素。参见图5，噪点个数越多得分越少。如果像素点A点，与周围8临域像素值差别很大则判定为噪点，噪点检测时忽略边缘点的检测。
所述检测噪点个数的公式如下：
Figure PCTCN2014089902-appb-000004
其中，Lp(c)表示噪点向量和，c表示中心点A周围的8临域区域；xo(c)表示中心像素点的灰度值，xk(c)表示中心点A周围的临域像素点，N＝8。如果Lp(c)大于预设的判定阈值则判定此中心点为噪点。一个图片噪点个数越少，表示图片越美观，质量越高。
所述计算单元62，还用于将所述锐度平均值转换为锐度得分值，将所述噪点个数转换为噪点得分值，根据所述扩展EXIF信息确定对应的权重因子，利用所述权重因子、锐度得分值、噪点得分值，计算得到所述图片对应的质量参数。比如，锐度得分为S1，噪点得分为S2，对应的权重因子锐度得分值对应为a和噪点得分值对应b，图片最终得分记为S＝a*S1+b*S2。
其中，所述将所述锐度平均值转换为锐度得分值可以为：经过大量图片仿真，如果锐度值在[1100,1200]区间判定为5分，区间[1000,1100]判定为4分，区间[900，1000]判定为3分，区间[700,900]判定为2分，锐度低于700判定为1分。
所述计算单元62，还用于如果主体区域噪点个数为[0,10]判定为5分，[11,20]判定为4分，[21,35]判定为3分，[36,45判定为2，噪点个数超过45判定为1分。
其中，所述计算单元62，还用于提取所述扩展EXIF中的闪光灯参数(TAG_FLASH)，当根据所述闪光灯参数确定没开启闪光灯时，所述权重因子为第一组权重因子；否则，所述权重因子为第二组权重因子；比如，如果为0则没有开启闪光灯，1为开启闪光灯；如果未开启闪光灯，则确定第一组权重因子为a＝0.6、b＝0.4；如果开启闪光灯，相较与正常情况，照片更容易出现噪点问题，则第二组权重因子为a＝0.4、b＝0.6。
优选地，所述计算单元62，还用于根据所述质量参数对所述图片进行分级，得到所述图片对应的级别，比如，将质量参数得分区间为[4.5,5]判定为优秀，区间[3.5,4.4]判定为良好，[2.5,3.4]判定为一般，[1,2.4]判定为差。
所述计算单元62，还用于根据所述质量参数对所述图片进行分级，得到所述图片对应的级别；相应的，所述处理单元，具体用于将所述质量参数以图片的标识为索引存储至数据库；或者，将所述质量参数和所述图片的级别，以图片的标识为索引存储至数据库；以及当展示图片时，按照质量参数、或者所述图片的级别将所述图片进行展示。
根据所述质量参数对所述图片进行存储可以为：将所述质量参数以图片的标识为索引存储至数据库；或者，将所述质量参数和所述图片的级别存储至数据库；其中，所述图片的标识可以为所述图片的名称、或者所述图片的拍摄时间等。
根据所述质量参数对所述图片进行展示可以为：当展示图片时，按照质量参数、或者所述图片的级别将所述图片进行展示。如，用户打开图库需要浏览图片时，可以根据需要按照质量参数进行分级得到的结果，将数据库中的全部图片进行分级展示给用户浏览。进一步的，用户还可以在对图片进行展示时，根据所述图片的级别，对图片进行筛选、删除等操作。
在本申请所提供的几个实施例中，应该理解到，所揭露的设备和方法，可以通过其它的方式实现。以上所描述的设备实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，如：多个单元或组件可以结合，或可以集成到另一个系统，或一些特征可以忽略，或不执行。另外，所显示或讨论的各组成部分相互之间的耦合、或直接耦合、或通信连接可以是通过一些接口，设备或单元的间接耦合或通信连接，可以是电性的、机械的或其它形式的。
上述作为分离部件说明的单元可以是、或也可以不是物理上分开的，作为单元显示的部件可以是、或也可以不是物理单元，即可以位于一个地方，也可以分布到多个网络单元上；可以根据实际的需要选择其中的部分或全部单元来实现本实施例方案的目的。
另外，在本发明各实施例中的各功能单元可以全部集成在一个处理单元中，也可以是各单元分别单独作为一个单元，也可以两个或两个以上单元集成在一个单元中；上述集成的单元既可以采用硬件的形式实现，也可以采用硬件加软件功能单元的形式实现。
本领域普通技术人员可以理解：实现上述方法实施例的全部或部分步骤可以通过程序指令相关的硬件来完成，前述的程序可以存储于一计算机可读取存储介质中，该程序在执行时，执行包括上述方法实施例的步骤；而前述的存储介质包括：移动存储设备、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。
或者，本发明上述集成的单元如果以软件功能模块的形式实现并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。基于这样的理解，本发明实施例的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机、服务器、或者网络设备等)执行本发明各个实施例所述方法的全部或部分。而前述的存储介质包括：移动存储设备、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，仅为本发明的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明揭露的技术范围内，可 轻易想到变化或替换，都应涵盖在本发明的保护范围之内。因此，本发明的保护范围应以所述权利要求的保护范围为准。
工业实用性
本发明公开了一种图片处理方法及电子设备，通过扩展EXIF信息，在EXIF信息里记录图片的焦点坐标；通过读取对焦点坐标，以此为中心切割出图片主体区域；然后计算主体区域的锐度和噪点个数，进而确定图片对应的质量参数，还可以根据质量参数进行存储以及展示。可见，采用本发明提供的方案能够快速的确定图片质量，进而帮助用户进行图片的优选、筛选，方便用户查看。

Claims (10)

  1. 一种图片处理方法，所述方法包括：
    采集图片时，将所述图片对应的焦点坐标添加到所述图片对应的可交换图像文件EXIF信息中，得到扩展EXIF信息；
    根据所述扩展EXIF信息确定所述图片的主体区域；
    计算所述主体区域对应的锐度平均值、并检测所述主体区域的噪点个数；
    利用所述锐度平均值以及所述噪点个数，计算得到所述图片对应的质量参数，根据所述质量参数对所述图片进行存储或展示。
  2. 根据权利要求1所述的方法，其中，所述方法还包括：获取指定的焦点坐标；或者设置所述图片的中心坐标为焦点坐标。
  3. 根据权利要求1所述的方法，其中，所述利用所述锐度平均值以及所述噪点个数，计算得到所述图片对应的质量参数，包括：
    将所述锐度平均值转换为锐度得分值，将所述噪点个数转换为噪点得分值，根据所述扩展EXIF信息确定对应的权重因子，利用所述权重因子、锐度得分值、噪点得分值，计算得到所述图片对应的质量参数。
  4. 根据权利要求3所述的方法，其中，所述根据所述扩展EXIF信息确定对应的权重因子，包括：提取所述扩展EXIF中的闪光灯参数，当根据所述闪光灯参数确定没开启闪光灯时，所述权重因子为第一组权重因子；否则，所述权重因子为第二组权重因子。
  5. 根据权利要去1-4任一项所述的方法，其中，所述方法还包括：根据所述质量参数对所述图片进行分级，得到所述图片对应的级别；
    相应的，所述根据所述质量参数对所述图片进行存储为：将所述质量参数以图片的标识为索引存储至数据库；或者，将所述质量参数和所述图 片的级别，以图片的标识为索引存储至数据库；
    所述根据所述质量参数对所述图片进行展示为：当展示图片时，按照质量参数、或者所述图片的级别将所述图片进行展示。
  6. 一种电子设备，所述电子设备包括：
    处理单元，配置为采集图片时，将所述图片对应的焦点坐标添加到所述图片对应的EXIF信息中，得到扩展EXIF信息；根据所述扩展EXIF信息确定所述图片的主体区域；根据所述质量参数对所述图片进行存储或展示；
    计算单元，配置为计算所述主体区域对应的锐度平均值、并检测所述主体区域的噪点个数；利用所述锐度平均值以及所述噪点个数，计算得到所述图片对应的质量参数。
  7. 根据权利要求6所述的电子设备，其中，所述处理单元，配置为获取指定的焦点坐标；或者设置所述图片的中心坐标为焦点坐标。
  8. 根据权利要求6所述的电子设备，其中，所述计算单元，配置为将所述锐度平均值转换为锐度得分值，将所述噪点个数转换为噪点得分值，根据所述扩展EXIF信息确定对应的权重因子，利用所述权重因子、锐度得分值、噪点得分值，计算得到所述图片对应的质量参数。
  9. 根据权利要求8所述的电子设备，其中，所述计算单元，配置为提取所述扩展EXIF中的闪光灯参数，当根据所述闪光灯参数确定没开启闪光灯时，所述权重因子为第一组权重因子；否则，所述权重因子为第二组权重因子。
  10. 根据权利要去6-9任一项所述的方法，其中，所述计算单元，配置为根据所述质量参数对所述图片进行分级，得到所述图片对应的级别；
    相应的，所述处理单元，配置为将所述质量参数以图片的标识为索引存储至数据库；或者，将所述质量参数和所述图片的级别，以图片的标识 为索引存储至数据库；以及当展示图片时，按照质量参数、或者所述图片的级别将所述图片进行展示。
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