Combination of extrapolation filter-based intra prediction with other intra prediction

Abstract

In one implementation, we propose to improve intra prediction performance by blending the prediction from EIP (Extrapolation filter-based Intra Prediction) with predictions from EIP or non-EIP (directional, planar, DC intra prediction). In one example, this is done by taking N regular intra predictors, along with EIP prediction. Template analysis can be performed to select the modes to blend and the corresponding weights. In one implementation, we specifically propose to employ DIMD and TIMD template analysis. That is, EIP with DIMD and EIP with TIMD are used in combining EIP with other intra prediction modes.

Description

[0001] COMBINATION OF EXTRAPOLATION FILTER-BASED INTRA PREDICTION WITH OTHER INTRA PREDICTION

[0002] This application claims the priority to European Application No. 24305054.9, filed on 9 January 2024, which is incorporated herein by reference in its entirety.

[0003] TECHNICAL FIELD

[0004] [1] The present embodiments generally relate to a method and an apparatus for intra prediction in video encoding and decoding.

[0005] BACKGROUND

[0006] [2] 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.

[0007] SUMMARY

[0008] [3] According to one embodiment, a method of video decoding is presented, comprising: generating a first prediction for a block of a picture, based on an extrapolation filter-based intra prediction mode; generating a second prediction for said block, based on another intra prediction mode; blending said first prediction and said second prediction to form a prediction for said block; and decoding said block based on said prediction for said block.

[0009] [4] According to another embodiment, a method of video encoding is presented, comprising: generating a first prediction for a block of a picture, based on an extrapolation filter-based intra prediction mode; generating a second prediction for said block, based on another intra prediction mode; blending said first prediction and said second prediction to form a prediction for said block; and encoding said block based on said prediction for said block.

[0010] [5] According to another embodiment, an apparatus for video decoding is presented, comprising at least one memory and one or more processors, wherein said one or more processors are configured to: generate a first prediction for a block of a picture, based on an extrapolation filter-based intra prediction mode; generate a second prediction for said block, based on another intra prediction mode; blend said first prediction and said second prediction to form a prediction for said block; and decode said block based on said prediction for said block.

[0011] [6] According to another embodiment, an apparatus for video encoding is presented, comprising at least one memory and one or more processors, wherein said one or more processors are configured to: generate a first prediction for a block of a picture, based on an extrapolation filter-based intra prediction mode; generate a second prediction for said block, based on another intra prediction mode; blend said first prediction and said second prediction to form a prediction for said block; and encode said block based on said prediction for said block.

[0012] [7] One or more embodiments also provide a computer program comprising instructions which when executed by one or more processors cause the one or more processors to perform the encoding method or decoding method according to any of the embodiments described herein. One or more of the present embodiments also provide a computer readable storage medium having stored thereon instructions for encoding or decoding video data according to the methods described herein.

[0013] [8] One or more embodiments also provide a computer readable storage medium having stored thereon video data generated according to the methods described above. One or more embodiments also provide a method and apparatus for transmitting or receiving the video data generated according to the methods described herein.

[0014] BRIEF DESCRIPTION OF THE DRAWINGS

[0015] [9] FIG. 1 illustrates a block diagram of a system within which aspects of the present embodiments may be implemented.

[0016]

[0010] FIG. 2 illustrates a block diagram of an embodiment of a video encoder.

[0017]

[0011] FIG. 3 illustrates a block diagram of an embodiment of a video decoder.

[0018]

[0012] FIG. 4 illustrates spatial GPM (Geometric Partitioning Mode) candidates.

[0019]

[0013] FIG. 5 illustrates a GPM template.

[0020]

[0014] FIG. 6 illustrates three defined filter shapes with fifteen inputs and one output.

[0021]

[0015] FIG. 7 illustrates three types of the reconstructed areas for EIP.

[0016] FIG. 8 illustrates an example of generating predictions for different positions in the current block by a diagonal order.

[0022]

[0017] FIG. 9 illustrates a method of blending the EIP prediction of the current block and several other intra predictions of the current block to generate a prediction of the current block, according to an embodiment.

[0023] DETAILED DESCRIPTION

[0024]

[0018] 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.

[0025]

[0019] 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.

[0026]

[0020] 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.

[0027]

[0021] 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.

[0028]

[0022] In several 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, HEVC, or VVC.

[0029]

[0023] 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) an RF portion that receives an RF signal transmitted, for example, over the air by a broadcaster, (ii) a Composite input terminal, (iii) a USB input terminal, and / or (iv) an HDMI input terminal.

[0030]

[0024] 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.

[0031]

[0025] 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.

[0032]

[0026] 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.

[0027] 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.

[0033]

[0028] Data is streamed to the system 100, in various embodiments, using a Wi-Fi network such as IEEE 802. 11. The Wi-Fi signal of these embodiments is received over the communications channel 190 and the communications interface 150 which are adapted for WiFi 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.

[0034]

[0029] The system 100 may provide an output signal to various output devices, including a display 165, speakers 175, and other peripheral devices 185. The other peripheral devices 185 include, in various examples of embodiments, one or more of a stand-alone DVR, a disk player, a stereo system, a lighting system, and other devices that provide a function based on 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.

[0035]

[0030] 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.

[0036]

[0031] 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.

[0037]

[0032] In the present application, the terms “reconstructed” and “decoded” may be used interchangeably, the terms “encoded” or “coded” 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.

[0038]

[0033] 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 preprocessing, and attached to the bitstream.

[0039]

[0034] 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). 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 from the original image block.

[0040]

[0035] The prediction residuals are then transformed (225) and quantized (230). The quantized transform coefficients, as well as motion vectors and other syntax elements such as the picture partitioning information, are entropy coded (245) to output a bitstream. As a non-limiting example, context-based adaptive binary arithmetic coding (CABAC) can be used to encode syntax elements into the bitstream.

[0041]

[0036] The encoder can skip the transform and apply quantization directly to the nontransformed 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.

[0037] The encoder decodes an encoded block to provide a reference for further predictions. The quantized transform coefficients are de-quantized (240) 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).

[0042]

[0038] 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.

[0043]

[0039] 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 transform coefficients, 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 transform coefficients are de-quantized (340) and inverse transformed (350) to decode the prediction residuals. Combining (355) the decoded prediction residuals and the predicted 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.

[0044]

[0040] 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 preencoding processing (201). The post-decoding processing can use metadata derived in the preencoding processing and signaled in the bitstream.

[0045]

[0041] The Extrapolation filter-based Intra Prediction (EIP) is a new coding tool being studied in the exploration experiment (see an article by L. Xu et al., “EE2-2.7: An extrapolation filterbased intra prediction mode,” document JVET-AF0080, Joint Video Experts Team (JVET) of ITU-T SG 16 WP 3 and ISO / IEC JTC 1 / SC 29, 32nd Meeting, Hannover, DE, 13-20 October 2023, hereinafter “JVET-AF0080”). It is based on learning an extrapolation filter from the reconstructed template and applying the learned extrapolation filter to the current block to generate the prediction signal. Although this tool provides a significant coding gain, it is still under-exploited. For example, compared to regular intra prediction modes, this mode is used as a single predictor. That is, it is not used / blended with other intra prediction modes. In order to improve the prediction quality and therefore the coding gain, the present embodiments propose to overcome this limitation by proposing new blending modes combining EIP with other EIPs and / or other intra prediction modes.

[0046]

[0042] Decoder side intra mode derivation (DIMD)

[0047]

[0043] In ECM (Enhanced Compression Model), DIMD derives, from the gradients in a template of decoded reference samples of the current luminance CB to be encoded / decoded, the indices of N (< 5) intra prediction modes that are likely the best intra prediction modes for predicting the current luminance CB in terms of rate-distortion.

[0048]

[0044] As described in an article by M. Coban et al., “Algorithm description of Enhanced Compression Model 10 (ECM 10),” document JVET-AE2025, Joint Video Experts Team (JVET) of ITU-T SG 16 WP 3 and ISO / IEC JTC 1 / SC 29, 31st Meeting, Geneva, CH, 11-19 July 2023 (hereinafter “JVET-AE2025”), when Decoder side intra mode derivation (DIMD) is applied, up to five intra modes are derived from the reconstructed neighbor samples, and those five predictors are combined with the planar mode predictor with the weights derived from the histogram of oriented gradients as described in JVET-O0449 (see an article by T. Guionnet et al., “Non-CE3: Decoder-side Intra Mode Derivation with Prediction Fusion Using Planar,” Document JVET-O0449-v2, Joint Video Experts Team (JVET) of ITU-T SG 16 WP 3 and ISO / IEC JTC 1 / SC 29 / WG 11 15th Meeting: Gothenburg, SE, 3-12 July 2019, hereinafter “JVET-O0449”). The division operations in weight derivation are performed utilizing the same lookup table (LUT) based integerization scheme used by the Cross-component linear model (CCLM). For example, the division operation in the orientation calculation

[0049] Orient = Gy / Gxis computed by the following LUT-based scheme: x = Floor( Log2( Gx ) ) normDiff = ( ( Gx « 4 ) » x ) & 15 x += ( 3 + ( normDiff != 0 ) ? 1 : 0 ) Orient = (Gy * ( DivSigTable[ normDiff ] | 8 ) + ( 1 « ( x - 1 ) where

[0050] DivSigTable

[0016] = { 0, 7, 6, 5 ,5, 4, 4, 3, 3, 2, 2, 1, 1, 1, 1, 0 }.

[0051]

[0045] For a block of size W x H, the weight for each of the five derived modes is modified if one of the above and left histogram magnitudes is twice larger than the other one. In this case, the weights are location dependent and computed as follows:

[0052]

[0046] If the above histogram is twice the left, then:

[0053]

[0047] If the magnitude of the left histogram is twice larger than the one of the above histogram, then: where wDimdtis the unmodified uniform weight of the DIMD selected as in JVET-O0449, A;is pre-defined and set to 10.

[0054]

[0048] Derived intra modes are included into the primary list of intra most probable modes (MPM), so the DIMD process is performed before the MPM list is constructed. The primary derived intra mode of a DIMD block is stored with the block and is used for MPM list construction of the neighboring blocks.

[0055]

[0049] Finally, note the region of neighboring reconstructed samples used for computing the histogram of oriented gradients is modified compared to JVET-O0449 method, depending on reconstructed samples availability. The region of decoded reference samples of the current WxH luma CB is extended towards the above-right side if available, up to W additional columns. It is extended towards the bottom-left side if available, up to H additional rows.

[0056]

[0050] Template-based intra mode derivation (TIMD)

[0057]

[0051] Like DIMD, for the current luminance CB to be encoded / decoded, TIMD follows a two-step process: an intra prediction mode index derivation step involving a template of decoded reference samples of the current luminance CB and a step in which the current luminance CB is actually predicted. A template can be generated using a wtxH portion on the left side and a W*ht portion above the current WxH luminance CB. During the TIMD derivation step, a tested intra prediction mode predicts the template of the current luminance CB from the set of decoded reference samples of the template.

[0052] As described in JVET-AE2025, for each intra prediction mode in MPMs, as well as the wide-angle modes if the above-right and / or bottom-left reference samples are available, SATD (Sum of Absolute Transformed Differences) between the prediction and reconstruction samples of the template is calculated. First two intra prediction modes with the minimum SATD are selected as the TIMD modes. These two TIMD modes (model, mode2) are fused with the weights after applying the PDPC (Position Dependent intra Prediction Combination) process, and such weighted intra prediction is used to code the current CU. Position dependent intra prediction combination (PDPC) is included in the derivation of the TIMD modes.

[0058]

[0053] The costs of the two selected modes are compared: costMode2 < 2*costModel, where costModel is the cost of model (with the minimum SATD) and costMode2 is the cost of mode2 (with the second minimum SATD). If this condition is true, the fusion is applied, otherwise only mode 1 is used.

[0059]

[0054] Weights of the modes are computed from their SATD costs as follows: weightl = costMode2 / (costModel+ costMode2) weight2 = 1 - weightl

[0060]

[0055] The division operations are conducted using the same lookup table (LUT) based integerization scheme used by the CCLM.

[0061]

[0056] Intra prediction fusion

[0062]

[0057] As described in JVET-AE2025, this intra prediction method derives predicted samples as a weighted combination of multiple predictors generated from different reference lines. In this process multiple intra predictors are generated and then fused by weighted averaging. The process of deriving the predictors to be used in the fusion process is described as follows:

[0063] 1) For angular intra prediction modes including the single mode case of TIMD and DIMD, the proposed method derives intra prediction by weighting intra predictions obtained from multiple reference lines represented as p fusion =woPune +wiPune+i where Piineis the intra prediction from the default reference line and Pune+1is the prediction from the line above the default reference line. The weights are set as w0= 3 / 4 and Wi = 1 / 4.

[0064] 2) For TIMD mode with blending, piineis used for the first mode (w0= 1, w1= 0) and Pune+i is used f°rthe second mode (w0= 0, w1= 1). 3) For DIMD mode with blending, the number of predictors selected for a weighted average is increased from 3 to 6.

[0065]

[0058] Intra prediction fusion method is applied to luma blocks when angular intra mode has non-integer slope (required reference samples interpolation) and the block size is greater than 16. It is used with MRL (Multiple Reference Lines) and not applied for ISP coded blocks. In the method studied in the sub-test a, PDPC is applied for the intra prediction mode using the closest reference line to the current block.

[0066]

[0059] Spatial Geometric partitioning mode (SGPM)

[0067]

[0060] Spatial geometric partitioning mode (SGPM) is an intra mode that resembles the inter coding tool of geometric partitioning mode (GPM), where the two prediction parts are generated from intra predicted process. In this mode, a candidate list is built with each entry containing one partition split and two intra prediction modes as shown in FIG. 4. 26 partition modes and 3 intra prediction modes are used to form the combinations. The length of the candidate list is set equal to 16. The selected candidate index is signalled.

[0068]

[0061] The list is reordered using the template as shown in FIG. 5, where SAD (Sum of Absolute Differences) between the prediction and reconstruction of the template is used for ordering. The template size is fixed to 1.

[0069]

[0062] For each partition mode, an IPM list is derived for each part using the same intra-inter GPM list derivation. The IPM list size is set to 3. In the list, TIMD derived mode is replaced by 2 derived modes with horizontal and vertical orientations.

[0070]

[0063] The SGPM mode is applied with a restricted blocks size: 4 < width < 64, 4 < height < 64, width < height*8, height < width*8, width*height > 32.

[0071]

[0064] A PPS flag is coded to indicate whether no blending of two intra predictions is allowed. When this PPS flag is set to false, the following adaptive blending is also used for spatial GPM, where blending depth r is derived as follows:

[0072] • If min(width, height) = 4, 1 / 2T is selected,

[0073] • else if min( width, height) = 8, T is selected,

[0074] • else if min( width, height) = 16, 2T is selected,

[0075] • else if min( width, height) = 32, 4T is selected,

[0076] • else, 8T is selected.

[0077]

[0065] Otherwise (the PPS flag is set to true), 1 / 4T is always used for spatial GPM coded blocks to make sure no blending is used when SGPM block has partition angle completely horizontal or vertical, and much narrower blending width is used when the SGPM block has other partition angles. It is noted that the flag is set to true in current Common Test Conditions (CTC) for the screen content videos.

[0078]

[0066] Extrapolation filter-based Intra Prediction (EIP)

[0079]

[0067] The extrapolation filter-based intra prediction as described in JVET-AF0080 is processed in three steps. First, the extrapolation filter coefficients are derived from a neighboring reconstructed area of the current block or inherited from a previous EIP block. Second, the extrapolation process generates predicted signals from the top-left to bottom-right comer within the current block. Third, an intra prediction angle is derived by analyzing the gradient of the predicted block, and then the corresponding intra-mode is used to select the MTS (Multi Transform Selection), NSPT (Non-separable Primary Transform) and LFNST (Low-Frequency Non-Separable Transform) kernel for transformation.

[0080]

[0068] The application of EIP is restricted to blocks with sizes not greater than 32x32 and the luma component only.

[0081]

[0069] Obtaining the EIP filter

[0082]

[0070] Three EIP filter shapes shown in FIG. 6 are used. The corresponding EIP modes are denoted as complete, horizontal and vertical EIP modes, respectively.

[0083]

[0071] There are two ways to obtain the filter coefficients for the current CU. First, the coefficients can be derived from the neighboring reconstructed pixels, and second, they can also be inherited from the previously decoded blocks.

[0084]

[0072] Derivation of EIP coefficients

[0085]

[0073] The decoder decodes the relevant syntax elements to determine the selected type of reconstructed area and the filter shape for the current block. The selected filter moves in the selected reconstructed area either horizontally or vertically with a one-pixel step to construct the auto-correlation matrix and the cross-correlation vector, as shown in FIG. 7. Specifically, three types of the reconstructed areas are defined. The size of the reconstructed area depends on min(blockWidth, blockHeight) and the selected filter shape. For example, when the current block is an 8x8 block and the selected filter shape is 4x4. The aboveSize of the reconstructed area is equal to min(8, 8) + 4 - 1 = 11, and the leftSize of the reconstructed area is equal to min(8, 8) + 4 - 1 = 11.

[0074] The calculation of coefficients from the auto-correlation matrix and the crosscorrelation vector is the same as that in CCCM (Convolutional Cross-Component Model).

[0086]

[0075] Inheritance of the EIP filters

[0087]

[0076] The EIP merge mode is also used in JVET-AF0080. The filter shape and the filter coefficients can be inherited from the previous decoded blocks with EIP or EIP merge mode. The decoder decodes an EIP merge flag to decide whether the proposed merge mode is used when the current block uses the EIP mode. A merge index is further decoded when the EIP merge flag is true. The EIP merge list includes spatial adjacent and non-adjacent candidates, temporal candidates, and history candidates. The constructed EIP merge list can include up to 12 candidates and the list will be reduced to up to 6 candidates by the reordering process based on the SAD cost measured on an L-shape template with column width and row height equal to 1. In the SAD calculation, predictions of the template area by EIP filters are generated only from reconstructed (neighbouring and template) samples, allowing the EIP filters to be applied in parallel rather than sequentially.

[0088]

[0077] The positions and inclusion order of the spatial adjacent, temporal, non-adjacent, shifted temporal and history candidates are the same as those defined in ECM-10.0 for the Cross-component Prediction (CCP) merge prediction candidates.

[0089]

[0078] Prediction of the current block

[0090]

[0079] The EIP mode generates prediction values for the current block from the top-left position to the bottom-right position by a diagonal prediction order, as shown in FIG. 8.

[0091]

[0080] The calculation for the prediction values in JVET-AF0080 is shown as follows, where pred^x yis the predicted value at (x, y) in the current block, ctis the Ithcoefficient of the selected EIP filter, the index of the coefficients is from 0 to 14, t(z-o / / setx1,y-o / / seti'1) is a reconstructed or a predicted value used for the current position’s prediction, and offsetXi and offsetYi are the position offsets to the current position along x and y directions, respectively.

[0092]

[0081] Mapping to the LFNST / NSPT / MTS set

[0093]

[0082] The JVET-AF0080 method uses the DIMD process to derive an intra prediction mode of the current block based on the EIP predicted samples. Specifically, a horizontal gradient and a vertical gradient are calculated for each predicted sample to build a histogram of oriented gradient (HoG). Then the intra prediction mode corresponding to the largest histogram count is used to determine the LFNST, NSPT or MTS transform set.

[0094]

[0083] Proposed CU level syntax

[0084] The EIP related syntax is signaled at CU level. An example of EIP related syntax is shown in the following table.

[0095]

[0085] FIG. 9 illustrate a method of improving the prediction performance by blending the regular prediction (non-EIP, e.g., directional, planar, DC) with EIP one, according to an embodiment. This is done by taking N regular intra predictors, along with EIP prediction. Template analysis can be performed to select the modes to blend and the corresponding weights. In the following, the EIP as described in JVET-AF0080 is used. However, the method can be applied to a more general EIP where, for example, the filter size, filter coefficients and / or the EIP mode can be different than what are described in JVET-AF0080.

[0096]

[0086] In one implementation, we specifically propose to employ DIMD and TIMD template analysis. That is, the following combinations are proposed as a realization of the general idea of combining EIP with intra prediction modes:

[0097] - EIP with DIMD

[0098] - EIP with TIMD

[0099]

[0087] Combination of EIP with DIMD

[0100]

[0088] As described earlier, if the DIMD blending applies, DIMD prediction is performed by combining planar prediction with five angular predictions. In order to employ EIP, the following is proposed.

[0101]

[0089] Method 1 : Conditionally replacing planar mode

[0102]

[0090] In this method, instead of blending the planar mode with the angular modes obtained by template analysis of DIMD, EIP is used. That is, EIP can be blended with the angular modes since EIP is considers as non-angular mode like DC or planar one.

[0103]

[0091] The planar mode can be constantly replaced by EIP. Alternatively, template analysis can be used to decide whether either EIP or planar is used. That is, both EIP and planar are applied to the reconstructed template and a template cost, usually SATD, is used to compare the two predictions. The prediction with less SATD cost is selected and blended with the other angular predictions.

[0104]

[0092] The EIP mode considered here can be one of its 3 modes (complete, horizontal and vertical). In addition, all EIP modes from the merge candidates (local, non-local, history and temporal candidates) can be used. The template analysis is employed to select the best mode to replace the planar mode at both the encoder and decoder (no explicit signaling is needed).

[0105]

[0093] Method 2: Conditionally replacing other angular modes

[0106]

[0094] Instead of replacing the planar mode, the other angular modes can also be replaced. This is also done by employing the template analysis to select the best modes. That is, EIP and the other modes derived by DIMD process are applied to the reconstructed template and a template cost is used to compare the predictions. The predictors with the least costs, comprising EIP and other regular modes, are selected and blended according to DIMD blending process.

[0107]

[0095] The EIP mode considered here can be one of its 3 modes (complete, horizontal and vertical). In addition, all EIP modes from the merge candidates (local, non-local, history and temporal candidates) can be used. The template analysis is employed to select the best EIP modes to replace regular modes.

[0096] Method 3: choosing an EIP mode for blending depending on the location-dependency ofDIMD

[0108]

[0097] For a given block using DIMD, the weight for each of the five derived modes may be modified if one of the above and left histogram magnitudes is n times larger than the other one, e.g., n = 2. As another example, n = 3.

[0109]

[0098] If the above histogram magnitude is n times larger than the one of the left histogram magnitude, the weights may feature vertical relationship, i.e., depend on the coordinate y of the current pixel in the block to be predicted. In this case, the vertical EIP mode may be systematically chosen among the EIP complete mode, the EIP horizontal mode, and the EIP vertical mode for blending. If the left histogram magnitude is n times larger than the one of the above histogram magnitude, the weights may feature horizontal relationship, i.e., depend on the coordinate x of the current pixel in the block to be predicted. In this case, the horizontal EIP mode may be systematically chosen among the EIP complete mode, the EIP horizontal mode, and the EIP vertical mode for blending.

[0110]

[0099] Method 4: Add DIMD-EIP as a new mode

[0111]

[0100] The above methods modify the DIMD prediction of the current block by replacing some intra modes by EIP modes. To increase the encoder flexibility, it is proposed to signal a new mode, named DIMD-EIP, which indicates that DIMD is used in combination with EIP. If this flag is zero, regular DIMD is used. The following options are considered:

[0112]

[0101] Option 1: Signal this mode as sub-mode ofDIMD

[0113]

[0102] In this option, if DIMD is enabled for the current block, a flag is signaled to indicate if EIP is combined with DIMD. In this case, the EIP modes of the current block and / or the merge blocks are evaluated on a template to decide which one to select and combine with the other regular modes.

[0114]

[0103] Option 2: Signal this mode as sub-mode of EIP

[0115]

[0104] In this option, the flag is signaled to indicate if EIP is combined with DIMD only if EIP is enabled for this block. This option requires less signaling and less template analysis compared with the first one. It is because the combination of DIMD and EIP is only allowed if EIP mode is already selected by the encoder. That is, there is no need to perform template analysis to decide whether to use either planar mode or EIP mode. The selected EIP mode replaces the planar mode in this case.

[0105] Combination of EIP with TIMD

[0116]

[0106] TIMD derives two intra modes by evaluating several intra prediction modes on the reconstructed template and measures the template cost, usually SATD. The two modes associated to the two least costs are blended according to their template costs. To combine with EIP, the following methods are considered.

[0117]

[0107] Method 1 : Include EIP in TIMD

[0118]

[0108] Instead of evaluating solely the regular intra modes, it is proposed that EIP modes are also evaluated on the reconstructed template. The EIP modes correspond to the three EIP modes of the current block and / or the EIP modes of the merge candidates. The template cost of all the modes, including EIP ones, are compared to yield 2 modes with minimum costs. Those two modes can then be regular or EIP, depending on the template cost. The two modes are blended using the TIMD blending weights that are based on the template cost.

[0119]

[0109] An alternative method is to modify the TIMD mode such that always a non-angular mode is blended with other angular modes. The non-angular modes are planar / DC or EIP modes. The best mode of non-angular mode is selected according to the template distance, and the regular TIMD process is used to deduce the remaining 2 candidates.

[0120] [HO] Method 2: Add TIMD-EIP as a new mode

[0121] [Hl] The above method modifies the TIMD prediction of the current block by replacing some intra modes by EIP modes. To increase the encoder flexibility, it is proposed to signal a new mode, named TIMD-EIP, which indicates that TIMD is used in combination with EIP. If this flag is zero, regular TIMD is used.

[0122]

[0112] The flag is signaled only if EIP is enabled for this block. This option requires less signaling and less template analysis compared with the first one. It is because the combination of TIMD and EIP is only allowed if EIP mode is already selected by the encoder. That is, no need to perform template analysis to decide whether to use planar mode or EIP mode. The selected EIP mode replaces the planar mode in this case.

[0123]

[0113] EIP mode application

[0124]

[0114] In one method, the application of the EIP filter is done independently of the other blended modes (e.g., DIMD, TIMD). It means that the intra prediction are computed independently and then blended together.

[0115] In another method, the application of the EIP filter is done on the results of the blending of the prediction:

[0125] First, the predictions other than EIP are computed.

[0126] Then, for each sample, following the EIP process, each sample is computed using the EIP filter then blended with the other predictions. The samples used by the EIP process are the one after the blending in this case.

[0127]

[0116] 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., 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.

[0128]

[0117] Various methods and other aspects described in this application can be used to modify modules, for example, the intra prediction modules (260, 360), of a video encoder 200 and decoder 300 as shown in FIG. 2 and FIG. 3. 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.

[0129]

[0118] 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.

[0130]

[0119] Various implementations involve decoding. “Decoding,” as used in this application, may 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. 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.

[0120] Various implementations involve encoding. In an analogous way to the above discussion about “decoding”, “encoding” as used in this application may encompass all or part of the processes performed, for example, on an input video sequence in order to produce an encoded bitstream.

[0131]

[0121] The implementations and aspects described herein may 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 may also be implemented in other forms (for example, an apparatus or program). An apparatus may be implemented in, for example, appropriate hardware, software, and firmware. The methods may be implemented in, for example, an apparatus, 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, for example, computers, cell phones, portable / personal digital assistants (“PDAs”), and other devices that facilitate communication of information between end-users.

[0132]

[0122] 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.

[0133]

[0123] Additionally, this application may refer to “determining” various pieces of information. Determining the information may include one or more of, for example, estimating the information, calculating the information, predicting the information, or retrieving the information from memory.

[0134]

[0124] Further, this application may refer to “accessing” various pieces of information. Accessing the information may 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.

[0135]

[0125] 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 may 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, 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.

[0136]

[0126] 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 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). 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.

[0137]

[0127] 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 quantization matrix for de-quantization. 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.

[0138]

[0128] As will be evident to one of ordinary skill in the art, implementations may produce a variety of signals formatted to carry information that may be, for example, stored or transmitted. The information may include, for example, instructions for performing a method, or data produced by one of the described implementations. For example, a signal may be formatted to carry the bitstream of a described embodiment. Such a signal may be formatted, for example, as an electromagnetic wave (for example, using a radio frequency portion of spectrum) or as a baseband signal. The formatting may include, for example, encoding a data stream and modulating a carrier with the encoded data stream. The information that the signal carries may be, for example, analog or digital information. The signal may be transmitted over a variety of different wired or wireless links, as is known. The signal may be stored on a processor-readable medium.

Claims

CLAIMS1. A method of video decoding, comprising: generating a first prediction for a block of a picture, based on an extrapolation filterbased intra prediction mode; generating a second prediction for said block, based on another intra prediction mode; blending said first prediction and said second prediction to form a prediction for said block; and decoding said block based on said prediction for said block.

2. A method of video encoding, comprising: generating a first prediction for a block of a picture, based on an extrapolation filterbased intra prediction mode; generating a second prediction for said block, based on another intra prediction mode; blending said first prediction and said second prediction to form a prediction for said block; and encoding said block based on said prediction for said block.

3. An apparatus for video decoding, comprising at least one memory and one or more processors, wherein said one or more processors are configured to: generate a first prediction for a block of a picture, based on an extrapolation filter-based intra prediction mode; generate a second prediction for said block, based on another intra prediction mode; blend said first prediction and said second prediction to form a prediction for said block; and decode said block based on said prediction for said block.

4. An apparatus for video encoding, comprising at least one memory and one or more processors, wherein said one or more processors are configured to: generate a first prediction for a block of a picture, based on an extrapolation filter-based intra prediction mode; generate a second prediction for said block, based on another intra prediction mode; blend said first prediction and said second prediction to form a prediction for said block; andencode said block based on said prediction for said block.

5. The method of claim 1 or 2, or the apparatus of claim 3 or 4, wherein said second prediction for said block is based on another extrapolation filter-based intra prediction mode.

6. The method of claim 1 or 2, or the apparatus of claim 3 or 4, wherein said second prediction for said block is based on an intra prediction mode other than an extrapolation filterbased intra prediction mode.

7. The method of any one of claims 1, 2, 5 and 6, or the apparatus of any one of claims 3-6, wherein a template including neighboring samples is used to determine that said first prediction and said second prediction are to be generated.

8. The method of claim 7, or the apparatus of claim 7, wherein histograms of oriented gradients of said template are used in said determining.

9. The method of claim 8, or the apparatus of claim 8, wherein said another intra prediction mode is an angular intra prediction mode determined from said histograms of oriented gradients of said template.

10. The method of claim 8 or 9, further comprising, or the apparatus of any one of claims 8 and 9, wherein said one or more processors are further configured to perform: obtaining a plurality of angular intra prediction modes from said histograms of oriented gradients of said template; obtaining one or more extrapolation filter-based intra prediction modes; performing intra prediction for said template based on each mode of a set of intra prediction modes, said set of intra prediction modes including said plurality of angular intra prediction modes and said one or more extrapolation filter-based intra prediction modes; obtaining a respective cost between reconstructed samples of said template and prediction samples of said template from intra prediction for said template based on each mode of said set of intra prediction modes; and selecting modes from said set of intra prediction modes based on said respective costs.

11. The method of any one of claims 1, 2 and 5-10, or the apparatus of any one of claims 3-10, wherein said blending is based on a weighted sum of said first prediction and said second prediction.

12. The method of claim 11, or the apparatus of claim 11, wherein said weight is based on left and above histogram magnitudes.

13. The method of any one of claims 8-12, or the apparatus of any one of claims 8-12, wherein Decoder-side Intra Mode Derivation (DIMD) is used.

14. The method of claim 13, or the apparatus of claim 13, wherein a flag is signaled to indicate whether extrapolation filter-based intra prediction is combined with DIMD responsive to that DIMD is enabled.

15. The method of claim 13, or the apparatus of claim 13, wherein a flag is signaled to indicate whether extrapolation filter-based intra prediction is combined with DIMD responsive to that EIP is enabled.

16. The method of claim 7, or the apparatus of claim 7, wherein said extrapolation filter-based intra prediction mode and said another intra prediction mode are tested in said template to perform said determining.

17. The method of claim 16, further comprising, or the apparatus of claim 16, wherein said one or more processors are further configured to perform: obtaining a plurality of angular intra prediction modes that are different than extrapolation filter-based intra prediction modes; obtaining one or more extrapolation filter-based intra prediction modes; performing intra prediction for said template based on each mode of a set of intra prediction modes, said set of intra prediction modes including said plurality of angular intra prediction modes and said one or more extrapolation filter-based intra prediction modes; obtaining a respective cost between reconstructed samples of said template and prediction samples of said template from intra prediction for said template based on each mode of said set of intra prediction modes; and selecting modes from said set of intra prediction modes based on said respective costs.

18. The method of any one of claims 1, 2 and 5-17, or the apparatus of any one of claims 3-17, wherein Template-based Intra Mode Derivation (TIMD) is used.

19. The method of claim 18, or the apparatus of claim 18, wherein a flag is signaled to indicate whether extrapolation filter-based intra prediction is combined with TIMD responsive to that TIMD is enabled.

20. The method of claim 18, or the apparatus of claim 18, wherein a flag is signaled to indicate whether extrapolation filter-based intra prediction is combined with TIMD responsive to that EIP is enabled.

21. A signal comprising a bitstream, formed by performing the method of any one of claims 1, 2 and 5-20.

22. A computer readable storage medium having stored thereon instructions for encoding or decoding a video according to the method of any one of claims 1, 2 and 5-20.

Images