WO2025002821A1 - Amélioration de l'entraînement d'un filtre à boucle - Google Patents

Amélioration de l'entraînement d'un filtre à boucle Download PDF

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Publication number
WO2025002821A1
WO2025002821A1 PCT/EP2024/066320 EP2024066320W WO2025002821A1 WO 2025002821 A1 WO2025002821 A1 WO 2025002821A1 EP 2024066320 W EP2024066320 W EP 2024066320W WO 2025002821 A1 WO2025002821 A1 WO 2025002821A1
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WO
WIPO (PCT)
Prior art keywords
video
scaling factor
filter
correction value
signal
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Ceased
Application number
PCT/EP2024/066320
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English (en)
Inventor
Franck Galpin
Philippe Bordes
Thierry DUMAS
Guillaume Boisson
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InterDigital CE Patent Holdings SAS
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InterDigital CE Patent Holdings SAS
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Filing date
Publication date
Application filed by InterDigital CE Patent Holdings SAS filed Critical InterDigital CE Patent Holdings SAS
Priority to CN202480044060.5A priority Critical patent/CN121420544A/zh
Priority to EP24732308.2A priority patent/EP4736432A1/fr
Publication of WO2025002821A1 publication Critical patent/WO2025002821A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/80—Details of filtering operations specially adapted for video compression, e.g. for pixel interpolation
    • H04N19/82—Details of filtering operations specially adapted for video compression, e.g. for pixel interpolation involving filtering within a prediction loop
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/117—Filters, e.g. for pre-processing or post-processing
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H04N19/176—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a block, e.g. a macroblock
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/46—Embedding additional information in the video signal during the compression process

Definitions

  • At least one of the present embodiments generally relates to a method or an apparatus for video encoding or decoding, compression or decompression.
  • image and video coding schemes usually employ prediction, including motion vector prediction, and transform to leverage spatial and temporal redundancy in the video content.
  • prediction including motion vector prediction, and transform
  • intra or inter prediction is used to exploit the intra or inter frame correlation, then the differences between the original image and the predicted image, often denoted as prediction errors or prediction residuals, are transformed, quantized, and entropy coded.
  • the compressed data are decoded by inverse processes corresponding to the entropy coding, quantization, transform, and prediction.
  • At least one of the present embodiments generally relates to a method or an apparatus for video encoding or decoding, and more particularly, to a method or an apparatus for coding or decoding using regressive-based affine bi-prediction weights.
  • a method comprises steps for determining a correction value from a neural network; modulating the correction value with a scaling factor; and, filtering a reconstructed portion of video by adding the reconstructed portion of video to the modulated correction value.
  • the method comprises the aforementioned steps, implemented for encoding or decoding.
  • an apparatus comprising a processor.
  • the processor can be configured to operate on digital video data according to the aforementioned methods.
  • an apparatus comprising a processor.
  • the processor can be configured to encode a block of a video or decode video data by executing any of the aforementioned methods.
  • a device comprising an apparatus according to any of the decoding embodiments; and at least one of (i) an antenna configured to receive a signal, the signal including the video block, (ii) a band limiter configured to limit the received signal to a band of frequencies that includes the video block, or (iii) a display configured to display an output representative of a video block.
  • a non-transitory computer readable medium containing data content generated according to any of the described encoding embodiments or variants.
  • a signal comprising video data generated according to any of the described encoding embodiments or variants.
  • video data or a bitstream is formatted to include data content generated according to any of the described encoding embodiments or variants.
  • a computer program product comprising instructions which, when the program is executed by a computer, cause the computer to carry out any of the described decoding embodiments or variants.
  • Figure 1 illustrates an example loop filtering process in typical video codecs.
  • Figure 2 illustrates an example CNN loop filter process in NNVC.
  • Figure 3 illustrates an example learning process
  • Figure 4 illustrates an example of symmetrical filter (left) and filter rotation (right).
  • Figure 5 illustrates a modified model architecture used during training.
  • Figure 7 illustrates a model used for training with quantization.
  • Figure 8 illustrates an example of ALF computation.
  • Each CTU (Coding Tree Unit) is represented by a Coding Tree in the compressed domain. This is a quad-tree division of the CTU, where each leaf is called a Coding Unit (CU).
  • Each CU is then given some Intra or Inter prediction parameters (Prediction Info). To do so, it is spatially partitioned into one or more Prediction Units (PUs), each PU being assigned some prediction information.
  • the Intra or Inter coding mode is assigned on the CU level.
  • the described aspects focus on the compression of videos, particularly the (in-loop) post-filters applied to the pictures after the image or part of the image have been reconstructed.
  • video codecs such as HEVC or VVC
  • filters applied to the reconstructed samples of the video pictures, aiming at reducing the coding artifacts and reducing the distortion with the original picture.
  • DPF deblocking filter
  • SAO sample-adaptive offset
  • ALF adaptive loop filter
  • BF bilateral filter
  • DBF Hadamard filter
  • Diffusion filter An example of successive loop filtering steps, corresponding to the state-of-art video codec, is depicted in Figure 1.
  • 4 successive filters are applied: Bilateral filter, DBF, SAO and ALF.
  • the output is the reconstructed picture samples.
  • filters are in general based on two main processes (classification and filtering) which can be decomposed as pixels classification, encoder only: determination of filter parameters (ex: DBF, SAO, ALF but not BF), filter parameters coding/decoding (ex: DBF, SAO, ALF but not BF), and class-dependent filtering.
  • the described aspects propose a new post-filter based on Neural Networks (NN) that may replace one or several loop-filters, or may be added to the existing loop-filters.
  • NN Neural Networks
  • a convolutional NN is added to (or replaces some of) the loop filters, for example after the DBF filter.
  • Figure 2 shows an example of pipeline of loop filtering
  • the reconstructed frame is processed by the DBF (Deblocking).
  • the output is used as input 1 , as well as other inputs (for example the predicted frame, residuals, the partition map, the QP map etc.).
  • the frame is filtered (possibly per block) and a correction is produced.
  • This correction is modulated by a scale factor and added to the input.
  • the ALF filter is applied on the result and the final frame is output.
  • the CNN has been learnt offline on a large dataset of blocks.
  • MSE Mel Square Error
  • MAE mean absolute error
  • the in-loop ALF filter (adaptive loop filtering) is a linear filter whose purpose is to reduce coding artefacts on the reconstructed samples.
  • the coefficients “c n “of the filter are determined so that to minimize the mean square error between original samples “s(r)” and filtered samples “t(r)” by using Wiener-based adaptive filter technique.
  • Filter tap position offset ⁇ po, pi, ... PN-I ⁇ , where p n denotes the sample location offset to r of the n th filter tap.
  • the set of tap positions is called the filter “shape”.
  • K different filters are determined with the samples of each class.
  • the classification is made with Directionality and Activity values derived with local gradients.
  • the coefficients of the ALF may be coded in the bitstream so that they can be dynamically adapted to the video content. There are also some default coefficients and the encoder indicate which set of coefficients to be used per CTU.
  • Adding elements can include inserting elements in between existing elements, such as, for example, inserting amplifiers and an analog-to-digital converter.
  • the RF portion includes an antenna.
  • USB and/or HDMI terminals can include respective interface processors for connecting system 1000 to other electronic devices across USB and/or HDMI connections.
  • various aspects of input processing for example, Reed-Solomon error correction
  • aspects of USB or HDMI interface processing can be implemented within separate interface les or within processor 1010 as necessary.
  • the demodulated, error corrected, and demultiplexed stream is provided to various processing elements, including, for example, processor 1010, and encoder/decoder 1030 operating in combination with the memory and storage elements to process the datastream as necessary for presentation on an output device.
  • Various elements of system 1000 can be provided within an integrated housing, Within the integrated housing, the various elements can be interconnected and transmit data therebetween using suitable connection arrangement, for example, an internal bus as known in the art, including the Inter-IC (I2C) bus, wiring, and printed circuit boards.
  • I2C Inter-IC
  • the system 1000 includes communication interface 1050 that enables communication with other devices via communication channel 1060.
  • the communication interface 1050 can include, but is not limited to, a transceiver configured to transmit and to receive data over communication channel 1060.
  • the communication interface 1050 can include, but is not limited to, a modem or network card and the communication channel 1060 can be implemented, for example, within a wired and/or a wireless medium.
  • Wi-Fi Wireless Fidelity
  • IEEE 802.11 IEEE refers to the Institute of Electrical and Electronics Engineers
  • the Wi-Fi signal of these embodiments is received over the communications channel 1060 and the communications interface 1050 which are adapted for Wi-Fi communications.
  • the communications channel 1060 of these embodiments is typically connected to an access point or router that provides access to external networks including the Internet for allowing streaming applications and other over- the-top communications.
  • Other embodiments provide streamed data to the system 1000 using a set-top box that delivers the data over the HDMI connection of the input block 1130.
  • Still other embodiments provide streamed data to the system 1000 using the RF connection of the input block 1130.
  • various embodiments provide data in a non- streaming manner.
  • various embodiments use wireless networks other than Wi-Fi, for example a cellular network or a Bluetooth network.
  • control signals are communicated between the system 1000 and the display 1100, speakers 1110, or other peripheral devices 1120 using signaling such as AV. Link, Consumer Electronics Control (CEC), or other communications protocols that enable device-to-device control with or without user intervention.
  • the output devices can be communicatively coupled to system 1000 via dedicated connections through respective interfaces 1070, 1080, and 1090. Alternatively, the output devices can be connected to system 1000 using the communications channel 1060 via the communications interface 1050.
  • the display 1100 and speakers 1110 can be integrated in a single unit with the other components of system 1000 in an electronic device such as, for example, a television.
  • the display interface 1070 includes a display driver, such as, for example, a timing controller (T Con) chip.
  • the display 1100 and speaker 1110 can alternatively be separate from one or more of the other components, for example, if the RF portion of input 1130 is part of a separate set- top box.
  • the output signal can be provided via dedicated output connections, including, for example, HDMI ports, USB ports, or COMP outputs.
  • the embodiments can be carried out by computer software implemented by the processor 1010 or by hardware, or by a combination of hardware and software. As a nonlimiting example, the embodiments can be implemented by one or more integrated circuits.
  • the memory 1020 can be of any type appropriate to the technical environment and can be implemented using any appropriate data storage technology, such as optical memory devices, magnetic memory devices, semiconductor-based memory devices, fixed memory, and removable memory, as non-limiting examples.
  • the processor 1010 can be of any type appropriate to the technical environment, and can encompass one or more of microprocessors, general purpose computers, special purpose computers, and processors based on a multi-core architecture, as non-limiting examples.
  • decoding refers only to entropy decoding
  • decoding refers only to differential decoding
  • decoding refers to a combination of entropy decoding and differential decoding.
  • encoding can encompass all or part of the processes performed, for example, on an input video sequence to produce an encoded bitstream.
  • processes include one or more of the processes typically performed by an encoder, for example, partitioning, differential encoding, transformation, quantization, and entropy encoding.
  • processes also, or alternatively, include processes performed by an encoder of various implementations described in this application.
  • encoding refers only to entropy encoding
  • encoding refers only to differential encoding
  • encoding refers to a combination of differential encoding and entropy encoding.
  • syntax elements as used herein are descriptive terms. As such, they do not preclude the use of other syntax element names.
  • Various embodiments may refer to parametric models or rate distortion optimization.
  • the balance or trade-off between the rate and distortion is usually considered, often given the constraints of computational complexity. It can be measured through a Rate Distortion Optimization (RDO) metric, or through Least Mean Square (LMS), Mean of Absolute Errors (MAE), or other such measurements.
  • RDO Rate Distortion Optimization
  • LMS Least Mean Square
  • MAE Mean of Absolute Errors
  • Rate distortion optimization is usually formulated as minimizing a rate distortion function, which is a weighted sum of the rate and of the distortion. There are different approaches to solve the rate distortion optimization problem.
  • the approaches may be based on an extensive testing of all encoding options, including all considered modes or coding parameters values, with a complete evaluation of their coding cost and related distortion of the reconstructed signal after coding and decoding.
  • Faster approaches may also be used, to save encoding complexity, in particular with computation of an approximated distortion based on the prediction or the prediction residual signal, not the reconstructed one.
  • Mix of these two approaches can also be used, such as by using an approximated distortion for only some of the possible encoding options, and a complete distortion for other encoding options.
  • Other approaches only evaluate a subset of the possible encoding options. More generally, many approaches employ any of a variety of techniques to perform the optimization, but the optimization is not necessarily a complete evaluation of both the coding cost and related distortion.
  • the implementations and aspects described herein can be implemented in, for example, a method or a process, an apparatus, a software program, a data stream, or a signal. Even if only discussed in the context of a single form of implementation (for example, discussed only as a method), the implementation of features discussed can also be implemented in other forms (for example, an apparatus or program).
  • An apparatus can be implemented in, for example, appropriate hardware, software, and firmware.
  • the methods can be implemented in, for example, a processor, which refers to processing devices in general, including, for example, a computer, a microprocessor, an integrated circuit, or a programmable logic device. Processors also include communication devices, such as, for example, computers, cell phones, portable/personal digital assistants (“PDAs”), and other devices that facilitate communication of information between end-users.
  • PDAs portable/personal digital assistants
  • references to “one embodiment” or “an embodiment” or “one implementation” or “an implementation”, as well as other variations thereof, means that a particular feature, structure, characteristic, and so forth described in connection with the embodiment is included in at least one embodiment.
  • the appearances of the phrase “in one embodiment” or “in an embodiment” or “in one implementation” or “in an implementation”, as well any other variations, appearing in various places throughout this application are not necessarily all referring to the same embodiment.
  • Accessing the information can include one or more of, for example, receiving the information, retrieving the information (for example, from memory), storing the information, moving the information, copying the information, calculating the information, determining the information, predicting the information, or estimating the information.
  • this application may refer to “receiving” various pieces of information.
  • Receiving is, as with “accessing”, intended to be a broad term.
  • Receiving the information can include one or more of, for example, accessing the information, or retrieving the information (for example, from memory).
  • “receiving” is typically involved, in one way or another, during operations such as, for example, storing the information, processing the information, transmitting the information, moving the information, copying the information, erasing the information, calculating the information, determining the information, predicting the information, or estimating the information.
  • any of the following 7”, “and/or”, and “at least one of”, for example, in the cases of “A/B”, “A and/or B” and “at least one of A and B”, is intended to encompass the selection of the first listed option (A) only, or the selection of the second listed option (B) only, or the selection of both options (A and B).
  • such phrasing is intended to encompass the selection of the first listed option (A) only, or the selection of the second listed option (B) only, or the selection of the third listed option (C) only, or the selection of the first and the second listed options (A and B) only, or the selection of the first and third listed options (A and C) only, or the selection of the second and third listed options (B and C) only, or the selection of all three options (A and B and C).
  • This may be extended, as is clear to one of ordinary skill in this and related arts, for as many items as are listed.
  • the word “signal” refers to, among other things, indicating something to a corresponding decoder.
  • the encoder signals a particular one of a plurality of transforms, coding modes or flags.
  • the same transform, parameter, or mode is used at both the encoder side and the decoder side.
  • an encoder can transmit (explicit signaling) a particular parameter to the decoder so that the decoder can use the same particular parameter.
  • signaling can be used without transmitting (implicit signaling) to simply allow the decoder to know and select the particular parameter.
  • signaling can be accomplished in a variety of ways. For example, one or more syntax elements, flags, and so forth are used to signal information to a corresponding decoder in various embodiments. While the preceding relates to the verb form of the word “signal”, the word “signal” can also be used herein as a noun.
  • At least one embodiment comprises implementing a filtering operation using a neural network to determine a correction factor.
  • At least one embodiment comprises encoding or decoding a video block by using filtering in a reconstructed video path according to the described embodiments.
  • At least one embodiment comprises the above embodiment to implement an Adaptive Loop Filter.
  • At least one embodiment further comprises determining of a correction factor based on minimizing a distance between reconstructed samples and original samples of a portion of video. At least one embodiment further comprises the above embodiments wherein a clipping or rounding operation is performed before applying a scaling factor.
  • At least one embodiment further comprises the above embodiments wherein the scaling factor is signaled for each block of pixels.
  • At least one embodiment comprises the above embodiments wherein a value of the scaling factor is associated with a class of filter that is implemented.
  • At least one embodiment comprises any encoding or decoding operation based on the above operations.
  • At least one embodiment comprises performing encoding or decoding with the aforementioned methods on a sub-block.
  • At least one embodiment comprises a bitstream or signal that includes one or more of the described syntax elements, or variations thereof.
  • At least one embodiment comprises a bitstream or signal that includes syntax conveying information generated according to any of the embodiments described.
  • At least one embodiment comprises creating and/or transmitting and/or receiving and/or decoding according to any of the embodiments described.
  • At least one embodiment comprises a method, process, apparatus, medium storing instructions, medium storing data, or signal according to any of the embodiments described.
  • At least one embodiment comprises inserting in the signaling syntax elements that enable the decoder to determine decoding information in a manner corresponding to that used by an encoder.
  • At least one embodiment comprises creating and/or transmitting and/or receiving and/or decoding a bitstream or signal that includes one or more of the described syntax elements, or variations thereof.
  • At least one embodiment comprises a TV, set-top box, cell phone, tablet, or other electronic device that performs transform method(s) according to any of the embodiments described.
  • At least one embodiment comprises a TV, set-top box, cell phone, tablet, or other electronic device that performs transform method(s) determination according to any of the embodiments described, and that displays (e.g., using a monitor, screen, or other type of display) a resulting image.
  • At least one embodiment comprises a TV, set-top box, cell phone, tablet, or other electronic device that selects, bandlimits, or tunes (e.g., using a tuner) a channel to receive a signal including an encoded image, and performs transform method(s) according to any of the embodiments described.
  • At least one embodiment comprises a TV, set-top box, cell phone, tablet, or other electronic device that receives (e.g., using an antenna) a signal over the air that includes an encoded image, and performs transform method(s).

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  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Compression Or Coding Systems Of Tv Signals (AREA)

Abstract

L'invention concerne un post-filtre basé sur des réseaux neuronaux (NN) en vue de remplacer un ou plusieurs filtres à boucle ou qui peut être ajouté aux filtres à boucle existants. Un réseau neuronal convolutif est ajouté aux filtres à boucle, ou remplace certains des filtres à boucle. Selon un mode de réalisation, le filtre basé sur un réseau neuronal est appliqué pour mettre en œuvre un filtre à boucle adaptatif. Une phase d'apprentissage génère un facteur de correction et une mise à l'échelle est mise en œuvre sur le facteur de correction. Un filtrage différent peut être effectué sur la base d'un bloc ou par classe.
PCT/EP2024/066320 2023-06-29 2024-06-13 Amélioration de l'entraînement d'un filtre à boucle Ceased WO2025002821A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN202480044060.5A CN121420544A (zh) 2023-06-29 2024-06-13 环路滤波器训练改进
EP24732308.2A EP4736432A1 (fr) 2023-06-29 2024-06-13 Amélioration de l'entraînement d'un filtre à boucle

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EP23306062 2023-06-29

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Citations (3)

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Publication number Priority date Publication date Assignee Title
WO2022072239A1 (fr) * 2020-09-29 2022-04-07 Qualcomm Incorporated Procédé de filtrage pour codage vidéo
WO2022238967A1 (fr) * 2021-05-14 2022-11-17 Nokia Technologies Oy Procédé, appareil et produit programme d'ordinateur pour fournir un réseau neuronal réglé précisément
US20230188713A1 (en) * 2020-06-04 2023-06-15 Interdigital Vc Holdings France, Sas Neural network based filter in video coding

Patent Citations (3)

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Publication number Priority date Publication date Assignee Title
US20230188713A1 (en) * 2020-06-04 2023-06-15 Interdigital Vc Holdings France, Sas Neural network based filter in video coding
WO2022072239A1 (fr) * 2020-09-29 2022-04-07 Qualcomm Incorporated Procédé de filtrage pour codage vidéo
WO2022238967A1 (fr) * 2021-05-14 2022-11-17 Nokia Technologies Oy Procédé, appareil et produit programme d'ordinateur pour fournir un réseau neuronal réglé précisément

Non-Patent Citations (1)

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Title
LI (BYTEDANCE) Y ET AL: "EE1-1.7: Deep In-Loop Filter with Additional Input Information", no. JVET-AC0177 ; m61759, 5 January 2023 (2023-01-05), XP030306835, Retrieved from the Internet <URL:https://jvet-experts.org/doc_end_user/documents/29_Teleconference/wg11/JVET-AC0177-v1.zip JVET-AC0177-v1/JVET-AC0177.docx> [retrieved on 20230105] *

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