Skipping of quantization-constrained correction filter

Abstract

A method for correcting a filtered image block is disclosed. A reconstructed image block is filtered (1902) to obtain a filtered image block. A block of difference transform coefficients is obtained (1904) from the filtered image block and another image block. A correction function is applied (1906) on the block of difference transform coefficients to obtain a block of corrected transform coefficients. The block of difference transform coefficients is subtracted (1908) from the block of corrected transform coefficients to obtain a block of correction coefficients. It is determined (1910) that at least one correction coefficient is different from zero or that a sum of absolute value of the correction coefficients is above a value. The block of corrected transform coefficients is inverse transformed (1912) to obtain a correction block responsive to the determining. The another image block and the correction block are added (1914) to obtain a corrected image block.

Description

[0001]SKIPPING OF QUANTIZATION-CONSTRAINED CORRECTION FILTER CROSS REFERENCE TO RELATED APPLICATIONS This application claims the benefit of European Application No. 23307037.4, filed on November 23, 2023 which is incorporated herein by reference in its entirety. TECHNICAL FIELD At least one of the present embodiments generally relates to a method and an apparatus for correcting an image block after reconstruction and filtering. Other embodiments generally relate to encoding (decoding respectively) method and apparatus. BACKGROUND To achieve high compression efficiency, image and video coding schemes usually employ prediction and transform to leverage spatial and temporal redundancy in the video content. Generally, intra or inter prediction is used to exploit the intra or inter picture correlation, then the differences between the original block and the predicted block, often denoted as prediction errors or prediction residuals, are transformed, quantized, and entropy coded. To reconstruct the video, the compressed data are decoded by inverse processes corresponding to the entropy coding, quantization, transform, and prediction. SUMMARY In one implementation, a correction is applied on a reconstructed image block after at least one filtering to obtain a corrected image block. In an example, the correction is a quantization- constrained correction. In an example, the correction of the filtered image block uses a non- filtered version of the reconstructed image block or a prediction block. In one example, the correction may be skipped (i.e. not applied) for a block, e.g. if / when all correction coefficients for the block are null or if / when a sum of absolute value of the correction coefficients is below a value. In other examples, rate-distortion costs are compared either in the image domain or in the transform domain. BRIEF DESCRIPTION OF THE DRAWINGS FIG.1 illustrates a block diagram of a system within which aspects of the present embodiments may be implemented; FIG.2 illustrates a block diagram of an embodiment of a video encoder; FIG.3 illustrates a block diagram of an embodiment of a video decoder; FIG.4A illustrates the quantization and dequantization of a transform coefficient ; FIG.4B illustrates the quantization and dequantization of a transform coefficient ; FIG.5 depicts a flowchart of a method for reconstructing an image block according to a specific example; FIG. 6 depicts a flowchart of a method for correcting an image block after reconstruction and filtering according to a specific example ; FIG.7 illustrates an example of a correction function; FIG.8 illustrates another example of a correction function; FIGs 9-17 depict flowcharts of a method for correcting an image block after reconstruction and filtering according to various examples; FIGs 18-19 depict flowcharts of a decoding method according to various examples ; FIG. 20 depicts a flowchart of a method for correcting a filtered image according to another example; and FIGs 21-22 depict flowcharts of an encoding method according to various examples. DETAILED DESCRIPTION This application describes a variety of aspects, including tools, features, embodiments, models, approaches, etc. Many of these aspects are described with specificity and, at least to show the individual characteristics, are often described in a manner that may sound limiting. However, this is for purposes of clarity in description, and does not limit the application or scope of those aspects. Indeed, all of the different aspects can be combined and interchanged to provide further aspects. Moreover, the aspects can be combined and interchanged with aspects described in earlier filings as well. The aspects described and contemplated in this application can be implemented in many different forms. FIGs. 1, 2 and 3 below provide some embodiments, but other embodiments are contemplated and the discussion of FIGs. 1, 2 and 3 does not limit the breadth of the implementations. At least one of the aspects generally relates to video encoding and decoding, and at least one other aspect generally relates to transmitting a bitstream generated or encoded. These and other aspects can be implemented as a method, an apparatus, a computer readable storage medium having stored thereon instructions for encoding or decoding video data according to any of the methods described, and / or a computer readable storage medium having stored thereon a bitstream generated according to any of the methods described. In the present application, the terms “reconstructed” and “decoded” may be used interchangeably, the terms “encoded” or “coded” may be used interchangeably, the terms “pixel” and “sample” may be used interchangeably and the terms “image,” “picture” and “frame” may be used interchangeably. Usually, but not necessarily, the term “reconstructed” is used at the encoder side while “decoded” is used at the decoder side. In the present application, the terms “dequantization” and “scaling” may be used interchangeably. Various methods are described herein, and each of the methods comprises one or more steps or actions for achieving the described method. Unless a specific order of steps or actions is required for proper operation of the method, the order and / or use of specific steps and / or actions may be modified or combined. Additionally, terms such as “first”, “second”, etc. may be used in various embodiments to modify an element, component, step, operation, etc., such as, for example, a “first decoding” and a “second decoding”. Use of such terms does not imply an ordering to the modified operations unless specifically required. So, in this example, the first decoding need not be performed before the second decoding, and may occur, for example, before, during, or in an overlapping time period with the second decoding. For the sake of clarity, satisfying, failing to satisfy a condition and configuring condition parameter(s) are described throughout embodiments described herein as relative to a threshold (e.g., greater, or lower than), a (e.g., threshold) value, configuring the (e.g., threshold) value, etc.). For example, satisfying a condition may be described as being above a (e.g., threshold) value, and failing to satisfy a condition (e.g., performance criteria) may be described as being below a (e.g., threshold) value. Embodiments described herein are not limited to threshold- based conditions. Any kind of other condition and parameter(s) (such as e.g., belonging or not belonging to a range of values) may be applicable to embodiments described herein. The present aspects are not limited to VVC or HEVC, and can be applied, for example, to other standards and recommendations, whether pre-existing or future-developed, and extensions of any such standards and recommendations (including VVC and HEVC). Unless indicated otherwise, or technically precluded, the aspects described in this application can be used individually or in combination. FIG. 1 illustrates a block diagram of an example of a system in which various aspects and embodiments can be implemented. System 100 may be embodied as a device including the various components described below and is configured to perform one or more of the aspects described in this application. Examples of such devices, include, but are not limited to, various electronic devices such as personal computers, laptop computers, smartphones, tablet computers, digital multimedia set top boxes, digital television receivers, personal video recording systems, connected home appliances, and servers. Elements of system 100, singly or in combination, may be embodied in a single integrated circuit, multiple ICs, and / or discrete components. For example, in at least one embodiment, the processing and encoder / decoder elements of system 100 are distributed across multiple ICs and / or discrete components. In various embodiments, the system 100 is communicatively coupled to other systems, or to other electronic devices, via, for example, a communications bus or through dedicated input and / or output ports. In various embodiments, the system 100 is configured to implement one or more of the aspects described in this application. The system 100 includes at least one processor 110 configured to execute instructions loaded therein for implementing, for example, the various aspects described in this application. Processor 110 may include embedded memory, input output interface, and various other circuitries as known in the art. The system 100 includes at least one memory 120 (e.g., a volatile memory device, and / or a non-volatile memory device). System 100 includes a storage device 140, which may include non-volatile memory and / or volatile memory, including, but not limited to, EEPROM, ROM, PROM, RAM, DRAM, SRAM, flash, magnetic disk drive, and / or optical disk drive. The storage device 140 may include an internal storage device, an attached storage device, and / or a network accessible storage device, as non-limiting examples. System 100 includes an encoder / decoder module 130 configured, for example, to process data to provide an encoded video or decoded video, and the encoder / decoder module 130 may include its own processor and memory. The encoder / decoder module 130 represents module(s) that may be included in a device to perform the encoding and / or decoding functions. As is known, a device may include one or both of the encoding and decoding modules. Additionally, encoder / decoder module 130 may be implemented as a separate element of system 100 or may be incorporated within processor 110 as a combination of hardware and software as known to those skilled in the art. Program code to be loaded onto processor 110 or encoder / decoder 130 to perform the various aspects described in this application may be stored in storage device 140 and subsequently loaded onto memory 120 for execution by processor 110. In accordance with various embodiments, one or more of processor 110, memory 120, storage device 140, and encoder / decoder module 130 may store one or more of various items during the performance of the processes described in this application. Such stored items may include, but are not limited to, the input video, the decoded video or portions of the decoded video, the bitstream, matrices, variables, and intermediate or final results from the processing of equations, formulas, operations, and operational logic. In some embodiments, memory inside of the processor 110 and / or the encoder / decoder module 130 is used to store instructions and to provide working memory for processing that is needed during encoding or decoding. In other embodiments, however, a memory external to the processing device (for example, the processing device may be either the processor 110 or the encoder / decoder module 130) is used for one or more of these functions. The external memory may be the memory 120 and / or the storage device 140, for example, a dynamic volatile memory and / or a non-volatile flash memory. In several embodiments, an external non-volatile flash memory is used to store the operating system of a television. In at least one embodiment, a fast external dynamic volatile memory such as a RAM is used as working memory for video coding and decoding operations, such as for MPEG-2, (MPEG refers to the Moving Picture Experts Group, MPEG-2 is also referred to as ISO / IEC 13818, and 13818-1 is also known as H.222, and 13818-2 is also known as H.262), HEVC (HEVC refers to High Efficiency Video Coding, also known as H.265 and MPEG-H Part 2), or VVC (Versatile Video Coding, a new standard being developed by JVET, the Joint Video Experts Team). The input to the elements of system 100 may be provided through various input devices as indicated in block 105. Such input devices include, but are not limited to, (i) a radio frequency (RF) portion that receives an RF signal transmitted, for example, over the air by a broadcaster, (ii) a Component (COMP) input terminal (or a set of COMP input terminals), (iii) a Universal Serial Bus (USB) input terminal, and / or (iv) a High Definition Multimedia Interface (HDMI) input terminal. Other examples, not shown in FIG.1, include composite video. In various embodiments, the input devices of block 105 have associated respective input processing elements as known in the art. For example, the RF portion may be associated with elements suitable for (i) selecting a desired frequency (also referred to as selecting a signal, or band-limiting a signal to a band of frequencies), (ii) down converting the selected signal, (iii) band-limiting again to a narrower band of frequencies to select (for example) a signal frequency band which may be referred to as a channel in certain embodiments, (iv) demodulating the down converted and band-limited signal, (v) performing error correction, and (vi) demultiplexing to select the desired stream of data packets. The RF portion of various embodiments includes one or more elements to perform these functions, for example, frequency selectors, signal selectors, band-limiters, channel selectors, filters, downconverters, demodulators, error correctors, and demultiplexers. The RF portion may include a tuner that performs various of these functions, including, for example, down converting the received signal to a lower frequency (for example, an intermediate frequency or a near-baseband frequency) or to baseband. In one set-top box embodiment, the RF portion and its associated input processing element receives an RF signal transmitted over a wired (for example, cable) medium, and performs frequency selection by filtering, down converting, and filtering again to a desired frequency band. Various embodiments rearrange the order of the above-described (and other) elements, remove some of these elements, and / or add other elements performing similar or different functions. Adding elements may include inserting elements in between existing elements, for example, inserting amplifiers and an analog-to-digital converter. In various embodiments, the RF portion includes an antenna. Additionally, the USB and / or HDMI terminals may include respective interface processors for connecting system 100 to other electronic devices across USB and / or HDMI connections. It is to be understood that various aspects of input processing, for example, Reed-Solomon error correction, may be implemented, for example, within a separate input processing IC or within processor 110 as necessary. Similarly, aspects of USB or HDMI interface processing may be implemented within separate interface ICs or within processor 110 as necessary. The demodulated, error corrected, and demultiplexed stream is provided to various processing elements, including, for example, processor 110, and encoder / decoder 130 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 100 may be provided within an integrated housing, Within the integrated housing, the various elements may be interconnected and transmit data therebetween using suitable connection arrangement 115, for example, an internal bus as known in the art, including the I2C bus, wiring, and printed circuit boards. The system 100 includes communication interface 150 that enables communication with other devices via communication channel 190. The communication interface 150 may include, but is not limited to, a transceiver configured to transmit and to receive data over communication channel 190. The communication interface 150 may include, but is not limited to, a modem or network card and the communication channel 190 may be implemented, for example, within a wired and / or a wireless medium. Data is streamed to the system 100, in various embodiments, using a Wi-Fi network such as 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 190 and the communications interface 150 which are adapted for Wi-Fi communications. The communications channel 190 of these embodiments is typically connected to an access point or router that provides access to outside networks including the Internet for allowing streaming applications and other over-the-top communications. Other embodiments provide streamed data to the system 100 using a set-top box that delivers the data over the HDMI connection of the input block 105. Still other embodiments provide streamed data to the system 100 using the RF connection of the input block 105. As indicated above, various embodiments provide data in a non-streaming manner. Additionally, various embodiments use wireless networks other than Wi-Fi, for example a cellular network or a Bluetooth network. The system 100 may provide an output signal to various output devices, including a display 165, speakers 175, and other peripheral devices 185. The display 165 of various embodiments includes one or more of, for example, a touchscreen display, an organic light-emitting diode (OLED) display, a curved display, and / or a foldable display. The display 165 can be for a television, a tablet, a laptop, a cell phone (mobile phone), or other device. The display 165 can also be integrated with other components (for example, as in a smart phone), or separate (for example, an external monitor for a laptop). The other peripheral devices 185 include, in various examples of embodiments, one or more of a stand-alone digital video disc (or digital versatile disc) (DVR, for both terms), a disk player, a stereo system, and / or a lighting system. Various embodiments use one or more peripheral devices 185 that provide a function based on the output of the system 100. For example, a disk player performs the function of playing the output of the system 100. In various embodiments, control signals are communicated between the system 100 and the display 165, speakers 175, or other peripheral devices 185 using signaling such as AV. Link, CEC, or other communications protocols that enable device-to-device control with or without user intervention. The output devices may be communicatively coupled to system 100 via dedicated connections through respective interfaces 160, 170, and 180. Alternatively, the output devices may be connected to system 100 using the communications channel 190 via the communications interface 150. The display 165 and speakers 175 may be integrated in a single unit with the other components of system 100 in an electronic device, for example, a television. In various embodiments, the display interface 160 includes a display driver, for example, a timing controller (T Con) chip. The display 165 and speaker 175 may alternatively be separate from one or more of the other components, for example, if the RF portion of input 105 is part of a separate set-top box. In various embodiments in which the display 165 and speakers 175 are external components, the output signal may 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 110 or by hardware, or by a combination of hardware and software. As a non-limiting example, the embodiments can be implemented by one or more integrated circuits. The memory 120 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 110 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. FIG. 2 illustrates an example video encoder 200, such as a VVC (Versatile Video Coding) encoder. FIG. 2 may also illustrate an encoder in which improvements are made to the VVC standard or an encoder employing technologies similar to VVC. Before being encoded, the video sequence may go through pre-encoding processing (201), for example, applying a color transform to the input color picture (e.g., conversion from RGB 4:4:4 to YCbCr 4:2:0), or performing a remapping of the input picture components in order to get a signal distribution more resilient to compression (for instance using a histogram equalization of one of the color components). Metadata can be associated with the pre- processing and attached to the bitstream. In the encoder 200, a picture is encoded by the encoder elements as described below. The picture to be encoded is partitioned (202) and processed in units of, for example, CUs (Coding Units). Each unit is encoded using, for example, either an intra or inter mode. When a unit is encoded in an intra mode, it performs intra prediction (260), e.g. using an intra-prediction tool such as Decoder Side Intra Mode Derivation (DIMD). In an inter mode, motion estimation (275) and compensation (270) are performed. The encoder decides (205) which one of the intra mode or inter mode to use for encoding the unit, and indicates the intra / inter decision by, for example, a prediction mode flag. Prediction residuals are calculated, for example, by subtracting (210) the predicted block (a.k.a. prediction block) from the original image block. The prediction residuals are then transformed (225) into transform coefficients c (a.k.a prediction residual transform coefficients) which are quantized (230) into quantization indexes ^^^(a.k.a transform coefficient levels or quantized transform coefficients on the encoder side). The quantization levels (a.k.a quantization indexes) ^^^, as well as motion vectors and other syntax elements such as the picture partitioning information, are entropy coded (245) to output a bitstream. The encoder can skip the transform and apply quantization directly to the non-transformed residual signal. The encoder can bypass both transform and quantization, i.e., the residual is coded directly without the application of the transform or quantization processes. The encoder decodes an encoded block to provide a reference for further predictions. The quantized transform coefficients are de-quantized (240) (a.k.a. scaled) and inverse transformed (250) to decode prediction residuals. Combining (255) the decoded prediction residuals and the predicted block, an image block is reconstructed. In-loop filters (265) are applied to the reconstructed picture to perform, for example, deblocking / SAO (Sample Adaptive Offset) / ALF (Adaptive Loop Filter) filtering to reduce encoding artifacts. The filtered image is stored in a reference picture buffer (280). In-loop filters (265) are thus used to enhance reconstructed images before storing them in the reference picture buffer (280). In-loop filters form a whole family. Among them, deblocking filters (DBF) aim at reducing blocking artifacts occurring along block boundaries. Deblocking filters are usually designed to improve subjective quality, that is, the noticeability of such coding errors by the human psychovisual system. In usual video coding standards such as HEVC and VVC, deblocking filters are predetermined based on coding information (such as prediction modes, motion vectors, transform coefficients) and on local variations across block boundaries. On the other hand, adaptive loop filters (ALF) are learnt at encoder side in order to minimize a mean squared error with respect to source images, then the learned filter weights are encoded into the bitstream. Adaptive loop filters are usually applied at CTU-level, while deblocking filters are applied along block borders. In VVC and in ECM, the Adaptive Loop Filter (ALF) is the last in-loop filter that is applied to the reconstructed frame. It typically uses as input the samples of the reconstructed picture after all the other filters (e.g. DBF, SAO) have been applied. In some examples, the samples before deblocking filters are used as additional inputs for ALF. A final ALF sample may thus be obtained by weighting the regular ALF and the filter applied to the samples before the deblocking filter. Specifically, a filtered sample may be derived as follows : ^ଽ ଶ^ ே ^^^^^^,^^^ ^^^^^,^^^ ^ ^ ^ ^^ ^^^^^^ ^ ^^ ^ and a current sample ^^^^^,^^^, ^^^is a difference (e.g. a clipped difference) between an intermediate sample and the current sample ^^^^^,^^^ and ℎ^,^is a difference (e.g. a clipped difference)between a neighboring sample before DBF and the current sample ^^^^^,^^^ . The filtercoefficients ^^^ , ^^ ൌ 0, … 24 may be signaled in the bitstream.FIG. 3 illustrates a block diagram of an example video decoder 300. In the decoder 300, a bitstream is decoded by the decoder elements as described below. Video decoder 300 generally performs a decoding pass reciprocal to the encoding pass as described in FIG. 2. The encoder 200 also generally performs video decoding as part of encoding video data. In particular, the input of the decoder includes a video bitstream, which can be generated by video encoder 200. The bitstream is first entropy decoded (330) to obtain quantization levels ^^^(a.k.a. transform coefficient levels or quantization levels on the decoder side), prediction modes, motion vectors, and other coded information. The picture partition information indicates how the picture is partitioned. The decoder may therefore divide (335) the picture according to the decoded picture partitioning information. The quantization levels ^^^are de- quantized (340) into reconstructed transform coefficients ^^^. De-quantization is also named scaling. The reconstructed transform coefficients ^^^are inverse transformed (350) to obtain the prediction residuals. Combining (355) the prediction residuals and the predicted block (a.k.a. prediction block), an image block is reconstructed. The predicted block can be obtained (370) from intra prediction (360) or motion-compensated prediction (i.e., inter prediction) (375). In- loop filters (365) are applied to the reconstructed image. The filtered image is stored at a reference picture buffer (380). Note that, for a given picture, the contents of the reference picture buffer 380 on the decoder 300 side is identical to the contents of the reference picture buffer 280 on the encoder 200 side for the same picture. The decoded picture can further go through post-decoding processing (385), for example, an inverse color transform (e.g., conversion from YCbCr 4:2:0 to RGB 4:4:4) or an inverse remapping performing the inverse of the remapping process performed in the pre-encoding processing (201). The post-decoding processing can use metadata derived in the pre-encoding processing and signaled in the bitstream. HEVC and VVC standards specify conventional independent scalar quantization with Uniform Reconstruction Quantizers (URQs). The reconstructed transform coefficients ^^^of URQs are defined as integer multiples of a quantization step size ∆ (a.k.a. quantization step) which depends on a quantization parameter (QP). This integer specifies the associated transform coefficient level, which is transmitted in the bitstream as quantization levels ^^^(a.k.a as quantization index). On the decoder side, given a quantization level ^^^and a quantization step size ∆, a reconstructed transform coefficient ^^^may be obtained as follows : ^^^ ൌ ^^ି^൫^^^൯ ൌ ^^^ ൈ Δ (1)On the encoder side, given coefficient or more precisely a prediction residual transform coefficient) and a quantization step size ∆, a quantization level ^^^may be generated as follows : ^^^ ൌ ^^^^^^ ൌ ⌊^^^^^^^^^^ / ^^ ^ ^^⌋ ൈ ^^^^^^^^^^ ^2^where ⌊. ⌋ is a floor operation (i.e. rounding to a lower integer), ^^^^^^ is an absolute value, ^^^^^^is the sign function (i.e. returns 1 if c>0, -1 if c<0 and 0 if c=0), and ^^ is a parameter such that 0<a<1. With this quantization method, every quantization level ^^^is associated with quantization bounds ^^^^^^ொ൫^^^൯ and ^^^^^^ொ൫^^^൯ such that an original coefficient ^^ between^^^^^^ொ൫^^^൯ and to ^^^. Hence, assuming this quantization method is used and given a quantization level ^^^, an original coefficient ^^ associated with ^^ ^is known to be between ^^^^^^ொ൫^^^൯ and ^^^^^^ொ൫^^^൯, as illustrated in FIG. 4A. In the case of uniform quantization with quantization step size Δ and parameter ^^, the inferior and superior quantization bounds may be defined as follows: ൫^^^ െ ^^^^௫൯ ൈ ^^ ^^^^ ^^^ ^ 0^^^^^^ொ൫^^^൯ ൌ ^(3) ^^^ ^^^^ ^^ ൫^^^ െ ^^^^ ൯ ൈ ^^ ^^^^ ^^ ^ 0^^^^^ ^ ^ொ൫^^^൯ ൌ ^(4) ^^^ ^^^^ ^with minimum ൌ െ^^ and ^^^^௫ ൌ 1 െ^^ . This parameterization of the quantization bounds and reconstruction values is furtherillustrated in FIG.4B. The encoder may use alternative strategies to select the quantization levels ^^^. For example, rate distortion optimized quantization (RDOQ) optimizes the quantization levels accounting not only for the distortion (i.e., MSE), but also for the rate. In this case, it is no longer guaranteed that the original coefficients ^^ are between the bounds ^^^^^^ொ൫^^^൯and ^^^^^^ொ൫^^^൯.In the following, ^^ is assumed to be bounded by ^^^^^^ ொ൫^^^൯ and and ^^^^^^ொ൫^^^൯ can be determined on the decoder side scalar ^^ (a.k.a. scalar quantization operation) and its quantization parameter (QP). If the encoder uses quantization strategies that may break this assumption, such as RDOQ, the method remains applicable. Let us define a quantization constraint by the following equation: ^^^^^௫^ ൌ ^^^ ^5^where ^^ is a scalar quantization operation (a.k.a scalar quantizer), ^^^is the quantization level of a prediction residual transform coefficient c, and ^^௫is a reconstructed value of the corresponding transform coefficient c. When no in-loop or out-of-loop filter is applied to a reconstructed picture, each reconstructed transform coefficient ^^௫ is obtained as ^^௫ ൌ ^^^. Since^^^ ൌ ^^ି^^^^^^, its value is between the quantization bounds ^^^^^^൫^^^൯ and ^^^^^^൫^^^൯ as depictedon Therefore, in this case, the quantization ^^^^^^^ ൌ ^^^ is satisfied.Assuming that each quantization level is determined by the encoder as ^^^ ൌ ^^^^^^, where ^^ isthe original (unquantized) coefficient, then ^^^^^^^ ൌ ^^^^^^, which is a necessary condition toreconstruct the original coefficient ^^ without error. More generally, the absolute error |^^^ െ ^^|between a reconstructed coefficient and the corresponding original coefficient is such that 0 ^|^^^ െ ^^| ^ ^^^^^^ொ൫^^^൯ െ ^^^^^^ொ൫^^^൯. the reconstructed picture (e.g., with DBF, SAO, ALF, etc.), each coefficient ^^௫is defined as ^^௫=^^^, where ^^^is the corresponding prediction residual transform coefficient of the reconstructed and filtered picture (^^^may not be computed explicitly in video coding). In this case, the above quantization constraint may not be satisfied anymore by ^^௫, resulting in a loss of information. For example, the DBF filter improves the subjective quality by removing block discontinuities, but it may also remove some details in the filtered area at the borders of the blocks. As a result, for some coefficients, we may have ^^^ > ^^^^^^ொ൫^^^൯ or ^^^ ^ ^^^^^^ொ൫^^^൯ , and thus ^^൫^^^൯ ് ^^^ . Said otherwise, the quantizationconstraint is not in this case. This results in a sub-optimal MSE of the filtered picture since the corresponding original coefficient ^^ is expected to be in the range ^^^^^^^^^൫^^^^൯, ^^^^^^^^൫^^^^൯൧. Thus, ^^^ is necessarily different from the original coefficient ^^ (i.e. the error ห^^^ െ ^^ห is not bounded by ^^^^^^ொ൫^^^൯ െ ^^^^^^ொ൫^^^൯. Although theALF filter is designed to reduce the MSE between the and filtered picture, it does not guarantee that the quantization constraint ^^൫^^^൯ ൌ ^^^ is satisfiedfor every coefficient ^^^, hence potentially leading to sub- given that the quantization levels ^^^are known to both the encoder and the decoder. Applying a quantization-constrained correction on the prediction residual transform coefficients of the filtered picture ensures that the reconstructed and filtered picture is closer to the original picture in terms of MSE. The goal is to prevent the filters from losing information that could be inferred from the quantized transform coefficients signaled in the bitstream, while still preserving the filtering effect. To this aim, a quantization-constrained correction may be applied to an image block ^^^obtained by filtering a block ^^^previously obtained using conventional reconstruction steps in video coding, as illustrated by FIGs 5 and 6. FIG. 5 depicts a flowchart of a method for reconstructing an image block according to a specific embodiment. At step S500, quantization levels ^^^of a current block are dequantized to obtain reconstructed coefficients ^^^ ൌ ^^ି^^^^^^. Each quantization level ^^^ is assigned a position within the currentblock. The quantization levels ^^^may be obtained by entropy decoding encoded data representative of the image block to be reconstructed. In an example, the dequantization is a scalar dequantization by a dequantization function ^^ି^which is parameterized by a quantization parameter QP. At step S502, an inverse transform ^^ି^is applied to the reconstructed coefficients ^^^in order to obtain a prediction residual block. At step S504, an image block ^^^is reconstructed as the sum of the prediction residual block obtained at step S502 and a prediction block ^^^^^^^^. As mentioned with reference to FIG.2, the prediction block ^^^^^^^^ may be obtained by intra prediction or motion compensation of blocks of pictures stored in the reference picture buffer. At step S506, the reconstructed block ^^^may be filtered. The filters may be of various types, e.g. a deblocking filter, SAO, ALF, etc. The filtered block is denoted ^^^. FIG.6 depicts a flowchart of a method for correcting an image block after reconstruction and filtering according to a specific embodiment. The correction, also called quantization constrained correction and denoted QC, is applied to the image block ^^^. The correction QC first converts ^^^at S600 back to prediction residuals and compute transform coefficients ^^^at S602 in order to correct the values of these coefficients using a correction step S604. Thecorrection step S604 ensures that the quantization constraint ^^൫^^^^ ൯ ൌ ^^^ is satisfied for thecorrected transform coefficient ^^^^ . The corrected transform ^^^^ are then convertedback at S606 to obtain the corrected block ^^ொ^ிusing the inverse transform ^^ି^and the summation with the prediction block at S608. The steps of the correction QC are further detailed hereafter: At S600, ^^^is converted back to prediction residuals. To this aim, the prediction block pred is subtracted from the filtered image block ^^^in order to obtain a filtered prediction residual block. The prediction ^^^^^^^^ is equal to the prediction used at S504 in the reconstruction stage depicted on FIG.5. Therefore, the prediction block ^^^^^^^^ does not have to be computed again using the codec’s prediction mechanisms. Instead, the prediction block may be stored in a buffer during the reconstruction and reused for the QC correction. At S602, the filtered prediction residual block is then converted back to the transform domainusing the forward transform ^^ . In the case where several types of transforms or inversetransforms may be applied (e.g., DCT-II, DST-7, DCT-8), the QC correction uses the forwardtransform ^^ of the same type as the inverse transform ^^ି^ used at S502 during thereconstruction stage. For example, if a block X is reconstructed using the inverse of the DCT- II at S502, its corresponding block (i.e. the block of transform coefficients ^^^obtained from ^^^) in the QC correction is transformed with forward DCT-II. The forward transform thus produces a new block of prediction residual transform coefficients ^^^, named more simply transform coefficients ^^^, each located at a given position within the block. Each transform coefficient ^^^can thus be associated with the quantization level ^^^used during the reconstruction stage, and which is located at the same position within the block. At S604, each transform coefficient ^^^of the block of prediction residual transform coefficients is corrected to obtain a block of corrected prediction residual transform coefficients ^^^^ , namedmore simply corrected transform coefficient ^^^^ . Its corrected version ^^^^ is computed as ^^^^ ൌ^^^^^^^^^ொ^.^ୀ^^൧^^^^^, where ^^^^^^^^^ொ^.^ୀ^^^is a correction function (also called projection function correction function ensures that the constraint ^^൫^^^^ ൯ ൌ^^^is satisfied, where ^^^is the quantization level associated with ^^^, and where ^^ is quantizer associated with the scalar dequantizer ^^ି^used in the reconstruction stage at S500. The correction function can be defined as follows: ^^^^^^^^^ொ^.^ୀ^^^^^^^^ ൌ min^max ^^^^ , ^^^^^^ொ൫^^^൯^, ^^^^^^ொ൫^^^൯^ (6)This function is a on FIG. 7. With this definition, each corrected transform coefficient ^^^^ is always between the quantization bounds ^^^^^^ொ൫^^^൯ and ^^^^^^ொ൫^^^൯ ofthe quantization level ^^^ for the quantizer ^^. Hence ^^^^ satisfies ^^^ isalready within the quantization bounds, no correction is applied (i.e. ^^^^ ൌ ^^^), which preservesthe filtering effect. The correction function in Equation 6 is defined to enforce the quantization constraint while also minimizing the squared error ൫^^^ଶ ^െ ^^^൯between the corrected and the uncorrected coefficient. However, other functions may be used. For example, a more general clipping function can be defined as ^^^^ ൌ min^max ^^^^, ^^^^^^, ^^^^௫^ where the clipping bounds ^^^^^,^^^^௫ may be computed similarly to ^^^^^^ொ൫^^^൯ and ^^^^^^ொ൫^^^൯ using Equations 3 and 4respectively, but where the of the parameter ^^. For example, ^^^^^and ^^^^௫may be pre-determined parameters known to both the encoder and decoder. Note that using ^^^^^ and ^^^^௫ such that െ^^ ^ ^^^^^ ^ ^^^^௫ ^ 1 െ ^^ ensuresthat ^^^^^^ொ൫^^^൯ ^ ^^^^^ ^ ^^^^௫ ^ ^^^^^^ொ^^^^^ . Hence, assuming that ^^^ is computed with thequantization function in Equation 2 by the encoder, using such values of ^^^^^and ^^^^௫still ensures that the quantization constraint ^^൫^^^^ ൯ ൌ ^^^ is satisfied (since ^^^^^^ொ൫^^^൯ ^ ^^^^^ ^^^^^ ^ ^^^^௫ ^ ^^^^^^ொ^^^^^). If other methods are used by the RDOQ),it may be difficult to enforce the constraint ^^൫^^^^൯ ൌ ^^^ in practice (e.g., the quantization Qmay be computationally extensive, or may many parameters that are unknown to the decoder). Hence, for simplicity in such cases, a correction function may still be defined as a clipping function between bounds ^^^^^and ^^^^௫, which enforces a simpler constraint ^^^^௫^^^^^ ^ ^^^^^. However, in rate-distortion based quantization methods such as RDOQ, the originalcoefficient may not be between the bounds ^^^^^^ொ൫^^^൯ and ^^^^^^ொ൫^^^൯ defined in Equations 3 and 4. Hence, the clipping bounds ^^^^^, ^^^^௫may be computed using parameters ^^^^^and ^^^^௫that do not necessarily satisfy the condition െ^^ ^ ^^^^^ ^ ^^^^௫ ^ 1 െ ^^.In another example, a smooth version of the correction function ^^^^^^^^^ொ^.^ୀ^^^may be used such as: ^^^^^ି^ ^ൌ ^^ ⋅ tanh ^^^ ^ ^^, (7)with a scale ^^ ൌ^௨^ೂ^^^^ି^^^ೂ^^^^ ଶand an ଶ . This smooth function is illustrated and ^^ ^^௫may be used instead of the inferior and superior bounds ^^^^^^ொ൫^^^൯ and ^^^^^^ொ^^^^^ respectively for the computation of the scale and offset parameters ^^ and After enforcing the quantization-constraint in the residual transform domain, the correctedtransform coefficients ^^^^ are converted back to the image domain to obtain a final correctedimage block ^^ொ^ி. This is performed by first applying the inverse transform again at S606 to obtain a block of corrected prediction residuals. The same inverse transform ^^ି^is used as in the reconstruction stage at S502. Finally, at S608, the prediction block ^^^^^^^^ is added back to the block of corrected prediction residuals to obtain a corrected image block ^^ொ^ிwhich satisfies the quantization constraint. Computing the quantization constrained correction filter on a picture region that is larger than a single transform block (e.g. CTU, picture or slice) requires the prediction of all the blocks within the region to be available. However, in conventional video coding, a prediction block is only required during the reconstruction step of the corresponding transform block. Therefore, the prediction of the full region may not be stored for later use in the conventional pipeline. Applying the QC correction filter illustrated on FIG.6 thus requires additional storage for the prediction of the full region. In contrast, a method for decoding is described below with reference to FIG. 9 that makes it possible to perform QC correction filtering using the non-filtered reconstructed image block ^^^instead of the prediction block ^^^^^^^^. Since in-loop filters other than the first filter applied (i.e., DBF), such as ALF, may already use the samples before deblocking filter (i.e., samples of the non-filtered reconstructed picture), these samples can be reused when computing the proposed QC correction on the full region, without requiring additional storage. FIG.9 depicts a flowchart of a method for correcting an image block after reconstruction and filtering according to a specific example. Compared to the example depicted on FIG. 6, the transform coefficients ^^^may be computed without using the prediction block ^^^^^^^^ explicitly.Instead, a block of difference transform coefficients ^^^′ (also called filtering differencetransform coefficients) may be computed first, by a forward transform T at S702 to a difference block obtained at S700 as the difference between the filtered image block ^^^and the non-filtered image block ^^^, i.e. the reconstructed image block ^^^obtained prior to the filtering (S506) of FIG.5Given that ^^^ െ ^^^ ൌ ൫^^^ െ ^^^^^^^^൯ െ ^^^^ െ ^^^^^^^^^, and assuming that the transform ^^ is alinear operation, the following equation may be derived : ^^൫^^^ െ ^^^൯ ൌ ^^^^^^ െ ^^^^^^^^^ െ ^^^^^^ െ ^^^^^^^^^ (8)Since the transform of thedequantized quantization levels of the block Qି^^^^^^ , Equation (8) can be written in thetransform domain as ^^ᇱ^ ൌ ^^^ െ Qି^^^^^^. quantization levels of the block Qି^^^^^^being obtained at S704, each coefficient ^^ of the block may thus be obtained (e.g. ^computed) at S706 as follows: ^^ ᇱ ି^^ ൌ ^^^ ^ Q ^^^^^ (9)Said otherwise, the block of obtained by adding the block of dequantized quantization levels Qି^^^^^^ to the block of difference transform coefficients ^^^′. Since the reconstruction step depicted in FIG.5 already computes the reconstructed transformcoefficients ^^ as ^^ ൌ ^^ି^^^^ ି^^ ^ ^^ at S500, the value of ^^ ^^^^^ may be reused instead of beingrecomputed within the QC correction step. Said otherwise, S704 may be bypassed, e.g. skipped. At S708, a correction function may then be applied to the block of transform coefficients ^^^toobtain a corresponding block of corrected transform coefficients ^^^^ , where the correctionfunction may be defined for example as in Equation 6 or Equation 7. The correction function of Equation 6 corresponds to a clipping of the transform coefficients ^^^to ensure they arebetween ^^^^^^ொ൫^^^൯ and ^^^^^^ொ൫^^^൯ which are the quantization bounds associated with the^^^. At S710, each corrected transform coefficient ^^^^ of the block may then be converted back to ablock of corrected difference transform coefficients ^^^^ ′ (also called corrected filteringdifference transform coefficients) obtained as ^^^ ି^^ ′ ൌ ^^^^ െ Q ^^^^^.Said otherwise, the block of corrected ^^^^ ′ is obtained bysubtracting the block of dequantized quantization levels Qି^^^^^^ from the block of correctedtransform coefficients ^^^^ .At S712, the block of corrected difference transform coefficients ^^^^ ′ is inverse transformed byapplying a transform T-1to obtain a corrected difference block. T-1is the inverse of the transform T applied at S702. At S714, the final corrected image block ^^ொ^ிmay then be obtained by summing the output of S712, i.e. the corrected difference block, with the non-filtered reconstructed image block ^^^. In a variant, the difference transform coefficients ^^^′ may be obtained by first computing separately the transforms of the filtered image block ^^^and of the non-filtered reconstructed image block ^^^. The difference transform coefficients ^^^′ are then obtained as the difference between the transform coefficients of ^^^and those of ^^^. FIG.10 depicts a flowchart of a method for correcting an image block after reconstruction and filtering according to another specific example. The steps of the method that are identical to the steps of FIG. 9 are identified with the same numeral references. In particular, the method comprises the steps S700, S702, S712 and S714. In this example, the difference transformcoefficients ^^ ′ may be directly corrected at ^ᇱ^ S709 as ^^^ ൌ ^^^^^^^^′^^^^′^ , where ^^^^^^^^′ is amodified correction function that may avoid the ^^^′ to ^^^ and from ^^^^to ^^^^ ′. Following the description of FIG.9 and FIG. 10, the modified correction function ^^^^^^^^′can be generally defined from the correction function ^^^^^^^^^ொ^.^ୀ^^൧as follows: ^^^ᇱ^ ൌ ^^^^^^^^ᇱ൫^^^′൯ ൌ ^^^^^^^^ ᇱ ି^ ି^^ொ^.^ୀ^^൧ ^^^^ ^ ^^ ൫^^^൯^ െ ^^ ൫^^^൯ (10)However, dequantized quantization level ^^ି^൫^^^൯ is not required to compute ^^^^ᇱ. For example, using the correction function ^^^^^^^^^ொ^.^ୀ^^൧as defined in Equation 6, the corresponding modified correction function ^^^^^^^^ᇱmay be defined as follows : ^^^^^^^^ᇱ൫^^^′൯ ൌ min ൬max ^^^^ᇱ,Δ^^^ ^௨^ொ ൫^^^൯^ ,Δொ ൫^^^൯^ ^11^where Δ^^^ ொ of the filtering difference transform coefficient associated with a quantization level ^^^. These bounds may be defined from the inferior and superior quantization bounds as Δ^^^ொ ൫^^^൯ ൌ ^^^^^^ொ൫^^^൯ െ^^൫^^^௨^^൯and Δ൫^^^൯ ൌ ^^^^^^ொ൫^^^൯ െ ^^ ൫^^^൯. However, the ^^^ ^ dequantized quantization level ^^ ൫^^^൯. For example, when ^^^^^^ொ൫^^^൯ and ^^^^^^ொ൫^^^൯ aredefined according to respectively, and given the 1, then the computation of the bounds can be simplified as Δ^^^ ^ொ ൫^^^൯ ൌ ^ ^Δ^^ ^^^^ ^and ^^^ ^^ ^ 0െΔ^^^^^ ^^^^ ^^^ ^ 0Δ^௨^ொ ^^^൯ ൌ ^ ^Δ^^ ^^^^ ^^. Hence, the value ^^ the bounds. Furthermore, in the case where ^^^^௫ ൌ ^^^(e.g., using ^^ ൌ 1 / 2 , we have ^^^^௫ ൌ 1 / 2 and ^^^^^ ൌ െ1 / 2), then we may directly computethe bounds as Δ^^^(^^ ^ ൌ ^௨^ொ ^ Δ ⋅ ^^^^^ and Δொ ൫^^^൯ ൌ Δ ⋅ ^^^^௫. In this case the bounds do notdepend on the quantization level ^^ if we consider a fixed quantization step Δ uniform quantization). Similar simplifications of the modified correction function ^^^^^^^^’ may be obtained for different equations of the correction function using the new bounds Δ^^^ ^௨^ொ ൫^^^൯ and Δொ൫^^^൯ which can be computed without using the dequantized considering the transform coefficient correction defined in the corresponding modified correction function ^^^^^^^^ᇱbecomes: ^^^^^^ ൫^^^′൯ ൌ ^^ ⋅ tanh ൬^ᇲି୭ᇲ^^^ᇱ ൌ ^^^ ᇱ ^^^ ^ ^^ᇱ, (12)^^^With the same scale ^൯ି^ೂ൫ ൯ , and using a modified offset ^^′ ൌ^ೞೠ^ೂ ൫^^൯ି^^^^ೂ ൫^^൯ ଶ . Considering the quantization bounds as defined inEquations 3 and 4, in the particular case where ^^ ൌ െ^^ , Δ ^௨^ ^^ ൌ^^^^^௫ ^^^ ொ ൫ ^൯ െΔொ൫^^^൯, hencethe modified offset ^^′ is equal to 0 and the scale becomes ^^ ൌ Δ ⋅ ^^^^௫, dependon the quantization level ^^^ (assuming uniform quantization with fixed step Δ^ as in theprevious example. In some cases, the QC correction might not significantly change the filtered image block (e.g. if the transform coefficients ^^^are already contained within the quantization bounds). In these cases, the extra inverse transform step S712 requires further computations that do not bring any improvement. In other cases, the QC correction may even degrade the MSE of a given block. For example, if RDOQ (Rate Distortion Optimization Quantization) is used, an original transform coefficient ^^ may not be between the quantization bounds ^^^^^^ொ൫^^^൯ and ^^^^^^ொ൫^^^൯.In this case, the QC correction function which forces the corrected transform coefficient ^^^^ tobe between these bounds may increase the error with the original coefficient. In contrast, a method for correcting a filtered image is disclosed below with reference to FIGs 11-18 that skips the QC correction based on fast decisions. In a first example, the reconstruction steps of the QC correction (including the inverse transform) may be skipped when QC correction has no effect or has an insignificant effect. This first example is applicable to both the encoder and the decoder. In other examples, the encoder may decide to enable or skip QC correction for a given region and inform the decoder of this decision by a flag signaled in the bitstream. Several variants comprise making skip decisions based on transform domain distortion computations. In some examples, intermediate QC correction computations initially made in the decision process may be stored for later reuse when applying QC correction if it is not skipped. FIG.11 depicts a flowchart of a method for correcting a filtered image according to a specific example. During the QC correction of a block, after correcting all the transform coefficient ^^^into their corrected versions ^^^^ , it is possible to detect if the QC correction has a significanteffect for the block directly in the transform domain, e.g. based on correction transform coefficients (e.g. a correction difference transform coefficients or more simply correctiondifference coefficients) ^^ௗ ൌ ^^^^ െ ^^^. In the case where the QC correction is detected to haveno significant effect, its computation can thus be aborted before performing the inverse transform of the corrected coefficients. Hence, initial steps of the QC correction are computed at S800 for a block to obtain thetransform coefficients ^^^ and the corresponding corrected transform coefficients ^^^^ . At S802,correction transform coefficients (e.g. a correction difference transform coefficients or moresimply correction difference coefficients) ^^ௗ are then computed as ^^ௗ ൌ ^^^^ െ ^^^. At S804, it ischecked whether all the correction transform coefficients ^^ௗin the block are null. If all the correction transform coefficients ^^ௗin the block are equal to zero, then the remaining steps of the QC correction (e.g., inverse transform) are skipped for the block at S806. In this case nomodification is applied to the filtered image block ^^^ (i.e., ^^ொ^ி ൌ ^^^ ). Otherwise, theremaining steps of the QC correction are applied at S808 normally to compute the final corrected image block ^^ொ^ி. FIG. 12 depicts a flowchart of a method for correcting a filtered image according to another specific example. The steps of the method that are identical to the steps of FIG.11 are identified with the same numeral references. In particular, the method comprises the steps S800, S802, S806 and S808. In this example, the QC correction is skipped if the coefficients ^^ௗhave small values, even if they are not all exactly equal to zero. For example, the decision whether or not to skip the correction may be performed by computing at S803 a sum ^^^^^^^^^^^^ of the absolute values of the coefficients ^^ௗand by comparing this sum to a value ^^ℎ at S805. The QC correction is skipped at S806 for the block if ^^^^^^^^^^^^ is lower than ^^ℎ. Otherwise, the remaining steps of the QC correction are applied at S808 normally to compute the final corrected image block ^^ொ^ி. The methods illustrated by FIG.11 and FIG.12 can also be applied in the case where the QC correction is computed using the non-filtered reconstructed image block ^^^instead of the prediction block ^^^^^^^^. In this case, the correction difference coefficient ^^ௗmay be computedas ^^ ൌ ^^^ ᇱ െ ^^ ′ where ^ᇱௗ^ ^ ^^′ is the difference transform coefficients, and ^^^^is its corrected version obtained using the modified correction function ^^^^^^^^ᇱas illustrated on FIG.10. The decision whether to skip or not the QC correction is then made similarly using the correction transform coefficients ^^ௗ. The methods illustrated by FIGs 11 and 12 may be performed the same way in the encoder and in the decoder. Deciding whether the QC correction degrades the result requires the original image which is only known to the encoder. Therefore, in other examples, the encoder decides to either skip or apply the QC correction in a region (e.g., CTU, slice, picture, …). For example, the decision of either applying or not applying the QC correction may be performed based on a distortion, but other criterions may be used such as a rate-distortion, additionally taking the rate into account, or a complexity criterion. If QC correction is applied, a flag may be signaled in the bitstream. A decoder parsing (e.g. decoding) the flag is thus able to decide whether the QC correction is to be applied or not to the region. FIG.13 depicts a flowchart of a method that may be applied in an encoder to decide whether or not to apply a QC correction to a region according to a first example. At S900, a rate- distortion cost rdCostNoQC is computed without applying (i.e. by skipping) the QC correction to the region. At S902, a rate-distortion cost rdCostQC is computed with the QC correction applied to the region. At S904, if the rate-distortion cost rdCostQC is lower than rdCostNoQC, then the QC correction is applied to the region at S906. At S908, a flag enableQCFlag is set to 1 to indicate to the decoder that QC correction is to be applied to the region. Otherwise, no correction is performed, and the flag is set to 0 at S910. The value of the flag is then written (e.g. signaled or encoded) in the bitstream at S912. The rate-distortion cost of a given mode is typically computed as rdCost = D +λ.R, where D is the distortion (e.g. MSE, Sum of Squared Errors (SSE), ...) of the reconstructed region, R is the rate associated with the mode (e.g. number of bits to code the flag enableQCflag), and λ is a Lagrangian parameter also referred as lambda. The values of the flag may be different, e.g. a value 1 may indicate that no QC correction is to be applied to the region and a value 0 that QC correction is to be applied to the region. FIG. 14 depicts a flowchart of a method that may be applied in an encoder to decide whether or not to apply a QC correction in a region according to a second example. The steps of the method that are identical to the steps of FIG.13 are identified with the same numeral references. In particular, the method comprises the steps S900, S904 and S908-S912. The step S902 is modified and comprises S902-1, S902-2 and S902-3. In this example, the QC corrected region is stored so that the pixel values may be reused in step S907. This avoids recomputing the QC correction of the region. At S902-1, the region is corrected by applying the QC correction to the region. In this case, the QC corrected region may be also stored for later use, e.g. at S907. At S902-2, the distortion distQC of the QC corrected region is computed. At S902-3, rdCostQC is computed from the distortion distQC of the QC corrected region and the rate rateQC associated with the encoding of this region, Said otherwise, rdCostQC= distQC+lambda* rateQC, where lambda is a Lagrangian parameter. At S904, if the rate-distortion cost rdCostQC is lower than rdCostNoQC, then, at S907, the pixel values of the reconstructed region are set equal to those of the stored QC corrected region without re-computing QC correction. At S908, a flag enableQCFlag is set to 1 to indicate to the decoder that QC correction is to be applied to the region. Otherwise, no correction is performed, and the flag is set to 0 at S910. The value of the flag is then written (e.g. signaled or encoded) in the bitstream at S912. In a variant, the distortion is computed in a transform domain, e.g. using the transform coefficients derived within the QC correction. This avoids the need to compute the inverse transform of each block of corrected coefficients in the region. It can be noted that since the transforms used in video coding (e.g., DCT) are typically orthogonal, computing the distortion in the transform domain or in the pixel domain is mathematically equivalent for the case of SSE or MSE. For other distortion metrics such as the sum of absolute differences (SAD), although different results may be obtained when computed in the transform domain, the variant may still be applied, e.g., the distortion may be computed as the sum of absolute transformed differences (SATD). FIG. 15 depicts a flowchart of a method that may be applied in an encoder to decide whether or not to apply a QC correction in a region based on an SSE distortion computed in the transform domain. At S1000, the SSE of the QC corrected region sseQC and the SSE of the non-corrected region sseNoQC are intialized, e.g. to 0. A first transform block in the region is also selected. The following steps are applied to each transform block in the region. More precisely, the region is partitioned into transform blocks that are reconstructed and filtered. The prediction residual transform coefficients ^^^of the filtered block ^^^corresponding to theselected transform block are computed at S1002, and their corrected versions ^^^^ are obtainedusing the QC correction function ^^^^^^^^^ொ^.^ୀ^^^. The transform coefficients ^^ of each original image block in the region are also used to compute the distortion in the transform domain and are thus obtained at S1004. These original coefficients ^^ may be either computed by applying the transform T on the prediction residual obtained between the original image block X and the prediction pred or reused from previous encoding steps (e.g., original transform coefficients are previously computed by the encoder before applying quantization). A SSE associated with the corrected image block, denoted sseTbQC, is then computed at S1006 in the transformdomain as the sum of squared error between the corrected coefficients ^^^^ and the originalcoefficients ^^ . Similarly, a SSE associated with the non-corrected image block, denotedsseTbNoQC, is computed at S1006 in the transform domain as the sum of squared errorbetween the non-corrected coefficients ^^^ and the original coefficients ^^ . The values ofsseTbQC and sseTbNoQC are then added to the SSE of the QC corrected region sseQC and the SSE of the non-corrected region sseNoQC respectively at S1008. The method steps are repeated with a next transform block in the region if any (S1010 and S1012). After these steps have been performed for all the transform blocks in the region, the rate distortion cost rdCostQC and rdCostNoQC are computed at S1014 using the corresponding SSE distortion values sseTbQC and sseTbNoQC respectively. The decision to apply or skip the QC correction for the region is then made using the rate-distortion costs rdCostQC and rdCostNoQC as in FIG. 13. More precisely, at S1016, if the rate-distortion cost rdCostQC is lower than rdCostNoQC, then the QC correction is applied to all transform blocks in the region at S1018. At S1020, a flag enableQCFlag is set to 1 to indicate to the decoder that QC correction is to be applied to all transform blocks in the region. Otherwise, no correction is performed, and the flag is set to 0 at S1022. The value of the flag is then written (e.g. signaled or encoded) in the bitstream at S1024. The values of the flag may be different, e.g. a value 1 may indicate that no QC correction is to be applied to the region and a value 0 that QC correction is to be applied to the region. In this variant, the SSE computation of each transform block can also be adapted to the case where the QC correction is computed using the non-filtered reconstructed image block ^^^instead of the prediction block ^^^^^^^^. In this case, the difference transform coefficients ^^^′ are computed instead of the prediction residual transform coefficients ^^^, and the corresponding corrected coefficients ^^^ᇱ^ are obtained by applying the modified correction function ^^^^^^^^′.Since the coefficients ^^^ ’ are the transform coefficients of ^^^ െ ^^^ (i.e., difference betweenfiltered and non-filtered reconstructed image blocks), the original coefficients used at S1006 tocompute the SSEs are not the transform coefficients c of the prediction residual ^^ െ ^^^^^^^^. Instead, the original coefficients denoted c’ may be computed as the transform coefficients of^^ െ ^^^ (i.e., difference between the original and the non-filtered reconstructed image block).Equivalently, the coefficients ^^’ may be obtained from the coefficients ^^ and the quantizationlevels ^^ି^^^^ ^ as ^^’ ൌ ି^^ ^^ െ ^^ ^^^^^. For each Transform block in the region, the SSE valuessseTbQC and sseTbNoQC thus be computed respectively between the corrected coefficients ^^^ᇱ^ and ^^’, and between the non-corrected coefficients ^^^’ and ^^’. In another variant depicted on FIG. 16, further computations are saved by storing, at S1003,the corrected coefficients ^^^^ (or ^^^ ᇱ^ ^ initially computed for the SSE computation of eachtransform block in the region. corrected coefficients ^^^^ (or ^^^^ᇱ^ may then be used at S1017. The steps of the method that are identical to the steps of are identified with the same numeral references. If the decision is made to apply the QC correction to the region (i.e., if rdCostQC < rdCostNoQC), the QC correction is then performed by reconstructing at S1017 each transform block in the region from the corresponding stored corrected coefficients.For example, from the corrected prediction residual transform coefficients ^^^^ , a correctedimage block ^^ொ^ிis reconstructed as in FIG.6, by applying the inverse transform ^^ି^and by adding the prediction image block ^^^^^^^^. In another example, from the corrected difference transform coefficients ^^^^ᇱ, a corrected image block ^^ொ^ிis reconstructed as in FIG. 10, by applying the inverse transform ^^ି^and by adding the non-filtered reconstructed image block ^^^.In another example, the correction difference coefficient ^^ௗ are computed as ^^ௗ ൌ ^^^^ െ ^^^ (oras ^^ௗ ൌ ^^^ ᇱ^ െ ^^^′) and are stored at S1003 instead of the corrected coefficients ^^^^ (or ^^^^ ′^. Fromthese correction difference coefficient ^^ௗ, the corresponding corrected image block ^^ொ^ிcan be reconstructed as depicted in FIG. 17, by applying the inverse transform ^^ି^at S2000 and by adding the filtered image block ^^^at S2002. FIG. 18 depicts a flowchart of a method that may be applied on a decoder side to decide whether or not to apply a QC correction to a region. On the decoder side, the decision to apply or skip QC correction in a region is directly made by reading (e.g. parsing or decoding) at S3000 the flag enableQCflag from the bitstream. For example, if the value of enableQCflag is 1 at S3002, QC correction is applied to the region at S3004, otherwise the QC correction is skipped (i.e. not applied). FIG.19 depicts a flowchart of a decoding method 1800 according to an example. At 1802, a reconstructed image region is filtered to obtain a filtered image region. The region may be a CTU, a slice, a tile, etc. It may be filtered by DBF, ALF, SAO, etc. The region may be partitioned into one or more blocks. At 1804, information indicating that correction is to be applied to the filtered image region is obtained (e.g. is decoded from a received bitstream). The information may be a flag (e.g. a binary flag). At 1806, the filtered image region is corrected based on the information. As an example, in the case where the information obtained at 1804 indicates that correction is to be applied to the filtered image region, the filtered image region is corrected. The correction may comprise applying the steps of the method illustrated by FIGs 6, 9 or 10 on the blocks of the filtered image region. FIG. 20 depicts a flowchart of a method 1900 for correcting a filtered image according to another example. At 1902, a reconstructed image block is filtered to obtain a filtered image block.At 1904, a block of difference transform coefficients (e.g. ^^^, ^^^′) is obtained from the filteredimage block and another image block (e.g. a prediction block or the reconstructed image block). At 1906, a correction function is applied on the block of difference transform coefficients toobtain a block of corrected transform coefficients (e.g. ^^^ᇱ^, ^^^^^. In an example, the correction function is a clipping function. For example, the clipping function clips a value so that the clipped value is between a first bound and a second bound higher than the first bound. At 1908, the block of difference transform coefficients is subtracted from the block of corrected transform coefficients to obtain a block of correction coefficients. At 1910, it is determined that at least one correction coefficient is different from zero or that a sum of absolute value of the correction coefficients is above a value At 1912, responsive to the determining, the block of corrected transform coefficients is inverse transformed to obtain a correction block. At 1914, the another image block is added to the correction block to obtain a corrected image block (e.g. ^^ொ^ி). FIG.21 depicts a flowchart of an encoding method according to an example. At 2002, a reconstructed image region is filtered to obtain a filtered image region. The region may be a CTU, a slice, a tile, etc. It may be filtered by DBF, ALF, SAO, etc. The region may be partitioned into one or more blocks, e.g. into transform blocks. At 2004, the filtered image region is corrected to obtain a corrected image region. At 2006, a first rate-distortion cost is computed for the filtered image region. At 2008, a second rate-distortion cost is computed for the corrected image region. At 2010, it is determined that the first rate-distortion cost is above the second rate-distortion cost. At 2012, responsive to said determining, information is encoded to indicate correction is to be applied to said filtered image region. The information may be a flag (e.g. a binary flag). FIG.22 depicts a flowchart of an encoding method 2100 according to another example. At 2102, a reconstructed image region is filtered to obtain a filtered image region. The region may be a CTU, a slice, a tile, etc. It may be filtered by DBF, ALF, SAO, etc. At 2104, for at least one filtered image block of the filtered image region, a block of difference transform coefficients is obtained from the filtered image block and another image block. At 2106, a correction function is applied on the block of difference transform coefficients (e.g.^^^, ^^^′) to obtain a block of corrected transform coefficients (e.g. ^^^^ , ^^^^ᇱ^. a first rate-distortion cost is computed based on the corrected transform coefficients and original coefficients. At 2110, a second rate-distortion cost is computed based on the difference transform coefficients and original coefficients. At 2112, it is determined that the first rate-distortion cost is below the second rate-distortion cost. At 2114, based on said determining, information is encoded that indicates correction is to be applied to the filtered image region. The information may be a flag (e.g. a binary flag). In an example, the original coefficients are obtained from an original image block X corresponding to the at least one filtered image block by applying a transform T on a prediction residual, e.g. X-pred. In another example, the original coefficients are obtained by applying a transform T on a difference block X-Xr. An apparatus comprising one or more processors and at least one memory coupled to said one or more processors is disclosed wherein the one or more processors are configured to perform any of the previous methods. A computer program is disclosed that comprises program code instructions for implementing the method of any one of the examples when executed by a processor. A computer readable storage medium is disclosed that has stored thereon instructions for implementing the method of any one of the examples. Moreover, the present aspects are not limited to ECM, VVC or HEVC, and can be applied, for example, to other standards and recommendations, and extensions of any such standards and recommendations. Unless indicated otherwise, or technically precluded, the aspects described in this application can be used individually or in combination. Various numeric values are used in the present application. The specific values are for example purposes and the aspects described are not limited to these specific values. Note that syntax elements as used herein, such as terms in equations and algorithms, signal labels / names, etc., such as quantization levels, and so on, are descriptive terms. As such, they do not preclude the use of other syntax element names. Various implementations involve decoding. “Decoding”, as used in this application, can encompass all or part of the processes performed, for example, on a received encoded sequence in order to produce a final output suitable for display. In various embodiments, such processes include one or more of the processes typically performed by a decoder, for example, entropy decoding, inverse quantization, inverse transformation, and differential decoding. In various embodiments, such processes also, or alternatively, include processes performed by a decoder of various implementations described in this application, for example, reconstructing an image block, filtering the reconstructed image block, correcting (possibly after filtering) the image block, e.g. using the non-filtered reconstructed image block. As further examples, in one embodiment “decoding” refers only to entropy decoding, in another embodiment “decoding” refers only to differential decoding, and in another embodiment “decoding” refers to a combination of entropy decoding and differential decoding, and in another embodiment “decoding” refers to the whole reconstructing picture process including entropy decoding. Whether the phrase “decoding process” is intended to refer specifically to a subset of operations or generally to the broader decoding process will be clear based on the context of the specific descriptions and is believed to be well understood by those skilled in the art. Various implementations involve encoding. In an analogous way to the above discussion about “decoding”, “encoding” as used in this application can encompass all or part of the processes performed, for example, on an input video sequence in order to produce an encoded bitstream. In various embodiments, such processes include one or more of the processes typically performed by an encoder, for example, partitioning, differential encoding, transformation, quantization, and entropy encoding. In various embodiments, such processes also, or alternatively, include processes performed by an encoder of various implementations described in this application, for example, reconstructing an image block, filtering the reconstructed image block, correcting (possibly after filtering) the image block, e.g. using the non-filtered reconstructed image block. As further examples, in one embodiment “encoding” refers only to entropy encoding, in another embodiment “encoding” refers only to differential encoding, and in another embodiment “encoding” refers to a combination of differential encoding and entropy encoding. Whether the phrase “encoding process” is intended to refer specifically to a subset of operations or generally to the broader encoding process will be clear based on the context of the specific descriptions and is believed to be well understood by those skilled in the art. This disclosure has described various pieces of information, such as for example syntax, that can be transmitted or stored, for example. This information can be packaged or arranged in a variety of manners, including for example manners common in video standards such as putting the information into an SPS, a PPS, a NAL unit, a header (for example, a NAL unit header, or a slice header), or an SEI message. Other manners are also available, including for example manners common for system level or application level standards such as putting the information into one or more of the following: a. SDP (session description protocol), a format for describing multimedia communication sessions for the purposes of session announcement and session invitation, for example as described in RFCs and used in conjunction with RTP (Real-time Transport Protocol) transmission. b. DASH MPD (Media Presentation Description) Descriptors, for example as used in DASH and transmitted over HTTP, a Descriptor is associated with a Representation or collection of Representations to provide additional characteristic to the content Representation. c. RTP header extensions, for example as used during RTP streaming. d. ISO Base Media File Format, for example as used in OMAF and using boxes which are object-oriented building blocks defined by a unique type identifier and length also known as 'atoms' in some specifications. e. HLS (HTTP live Streaming) manifest transmitted over HTTP. A manifest can be associated, for example, to a version or collection of versions of a content to provide characteristics of the version or collection of versions. When a figure is presented as a flow diagram, it should be understood that it also provides a block diagram of a corresponding apparatus. Similarly, when a figure is presented as a block diagram, it should be understood that it also provides a flow diagram of a corresponding method / process. Some embodiments refer to rate distortion optimization. In particular, during the encoding process, the balance or trade-off between the rate and distortion is usually considered, often given the constraints of computational complexity. The 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. For example, 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. Reference 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. Thus, 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. Additionally, this application may refer to “determining” various pieces of information. Determining the information can include one or more of, for example, estimating the information, calculating the information, predicting the information, or retrieving the information from memory. Further, this application may refer to “accessing” various pieces of information. 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. Additionally, 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). Further, “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. It is to be appreciated that the use of any of the following “ / ”, “and / or”, and “at least one of”, for example, in the cases of “A / B”, “A and / or B” and “at 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). As a further example, in the cases of “A, B, and / or C” and “at least one of A, B, and C”, 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. Also, as used herein, the word “signal” refers to, among other things, indicating something to a corresponding decoder. For example, in certain embodiments the encoder signals a particular one of a plurality of quantization levels. In this way, in an embodiment the same parameter is used at both the encoder side and the decoder side. Thus, for example, an encoder can transmit (explicit signaling) a particular parameter to the decoder so that the decoder can use the same particular parameter. Conversely, if the decoder already has the particular parameter as well as others, then signaling can be used without transmitting (implicit signaling) to simply allow the decoder to know and select the particular parameter. By avoiding transmission of any actual functions, a bit savings is realized in various embodiments. It is to be appreciated that 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. As will be evident to one of ordinary skill in the art, implementations can produce a variety of signals formatted to carry information that can be, for example, stored or transmitted. The information can include, for example, instructions for performing a method, or data produced by one of the described implementations. For example, a signal can be formatted to carry the bitstream of a described embodiment. Such a signal can be formatted, for example, as an electromagnetic wave (for example, using a radio frequency portion of spectrum) or as a baseband signal. The formatting can include, for example, encoding a data stream and modulating a carrier with the encoded data stream. The information that the signal carries can be, for example, analog or digital information. The signal can be transmitted over a variety of different wired or wireless links, as is known. The signal can be stored on a processor-readable medium. A number of embodiments has been described above. Features of these embodiments can be provided alone or in any combination, across various claim categories and types.

Claims

CLAIMS 1. A method comprising: filtering a reconstructed image block to obtain a filtered image block ; obtaining a block of difference transform coefficients from the filtered image block and another image block; applying a correction function on the block of difference transform coefficients to obtain a block of corrected transform coefficients; subtracting the block of difference transform coefficients from the block of corrected transform coefficients to obtain a block of correction coefficients ; determining that at least one correction coefficient is different from zero or that a sum of absolute value of the correction coefficients is above a value ; inverse transforming the block of corrected transform coefficients to obtain a correction block responsive to the determining ; and adding the another image block and the correction block to obtain a corrected image block.

2. The method of claim 1, wherein the another image block is the reconstructed image block.

3. The method of claim 1, wherein the another image block is a prediction block.

4. An encoding method comprising: filtering a reconstructed image region to obtain a filtered image region ; correcting the filtered image region to obtain a corrected image region; computing a first rate-distortion cost for the filtered image region ; computing a second rate-distortion cost for the corrected image region ; determining that the first rate-distortion cost is above the second rate-distortion cost ; and encoding information indicating correction is to be applied to said filtered image region responsive to said determining.

5. An encoding method comprising: filtering a reconstructed image region to obtain a filtered image region partitioned into blocks ; obtaining, for at least one filtered image block of the filtered image region, a block of difference transform coefficients from the filtered image block and another image block;applying a correction function on the block of difference transform coefficients to obtain a block of corrected transform coefficients; computing a first rate-distortion cost based on the corrected transform coefficients and original coefficients ; computing a second rate-distortion cost based on the difference transform coefficients and original coefficients ; determining that the first rate-distortion cost is below the second rate-distortion cost ; and encoding information indicating correction is to be applied to said filtered image region based on said determining.

6. The method of claim 5, wherein the original coefficients are obtained from an original image block corresponding to the at least one filtered image block by applying a transform on a difference between the original image block and the another image block.

7. A decoding method comprising : filtering a reconstructed image region to obtain a filtered image region ; obtaining information indicating correction is to be applied to said filtered image region ; and correcting the filtered image region based on the information.

8. The method of claim 7, wherein correcting the filtered image region comprises for at least one filtered image block : obtaining a block of difference transform coefficients from the filtered image block and another image block; applying a correction function on the block of difference transform coefficients to obtain a block of corrected transform coefficients; inverse transforming the block of corrected transform coefficients to obtain a correction block; and adding the another image block and the correction block to obtain a corrected image block.

9. An apparatus comprising one or more processors and at least one memory coupled to said one or more processors, wherein said one or more processors are configured to perform the method of any one of claims 1-8.

10. A computer program comprising program code instructions for implementing the methodaccording to any one of claims 1-8 when executed by a processor.

11. A computer readable storage medium having stored thereon instructions for implementing the method of any one of claims 1-8.

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