Downscaling ratio prediction for reference picture resampling

Abstract

Methods and apparatus are provided for prediction of a downscaling ratio to use with reference picture resampling mode in a video compression or decompression system. In one embodiment, features are extracted from a video sequence and preprocessed before training a fully connected neural network. The fully connected neural network receives an input quantization information and outputs information to enable a subsampling decision for reference picture resampling to be performed. In another embodiment, a downscaling ratio is determined by interpolation based on a quantization parameter.

Description

[0001] DOWNSCALING RATIO PREDICTION FOR REFERENCE PICTURE RESAMPLING

[0002] TECHNICAL FIELD

[0003] At least one of the present embodiments generally relates to a method or an apparatus for video encoding or decoding, compression or decompression.

[0004] BACKGROUND

[0005] To achieve high compression efficiency, image and video coding schemes usually employ prediction, including motion vector 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 frame correlation, then the differences between the original image and the predicted image, often denoted as prediction errors or prediction residuals, are transformed, quantized, and entropy coded. To reconstruct the video, the compressed data are decoded by inverse processes corresponding to the entropy coding, quantization, transform, and prediction.

[0006] SUMMARY

[0007] At least one of the present embodiments generally relates to a method or an apparatus for video encoding or decoding, and more particularly, to a method or an apparatus for prediction of a downsampling ratio for reference picture resampling in an encoding or decoding process.

[0008] According to a first aspect, there is provided a method. The method comprises steps for extracting features from a video sequence; training a fully connected neural network using the extracted features to produce a quantization parameter switch point and quantization parameter offset; determining a subsampling decision for reference picture resampling mode based on the quantization parameter switch point and quantization parameter offset; and, encoding the video sequence in reference picture resampling mode using the subsampling decision.

[0009] According to a second aspect, there is provided another method. The method comprises steps for parsing video data from a video sequence for information indicative of picture size of a picture; determining a resampling ratio if said information indicates said picture has been resampled; and, decoding the video sequence in reference picture resampling mode using the picture size, a quantization parameter switch point and quantization parameter offset.

[0010] According to another aspect, there is provided an apparatus. The apparatus comprises a processor and a memory. The processor can be configured to operate on digital video data according to the aforementioned methods.

[0011] According to another aspect, there is provided an apparatus. The apparatus comprises a processor and a memory. The processor can be configured to encode a block of a video or decode video data by executing any of the aforementioned methods.

[0012] According to another general aspect of at least one embodiment, there is provided a device comprising an apparatus according to any of the decoding embodiments; and at least one of (i) an antenna configured to receive a signal, the signal including a video block, (ii) a band limiter configured to limit the received signal to a band of frequencies that includes a video block, or (iii) a display configured to display an output representative of a video block.

[0013] According to another general aspect of at least one embodiment, there is provided a non-transitory computer readable medium containing data content generated according to any of the described encoding embodiments or variants.

[0014] According to another general aspect of at least one embodiment, there is provided a signal comprising video data generated according to any of the described encoding embodiments or variants.

[0015] According to another general aspect of at least one embodiment, video data or a bitstream is formatted to include data content generated according to any of the described encoding embodiments or variants.

[0016] According to another general aspect of at least one embodiment, there is provided a computer program product comprising instructions which, when the program is executed by a computer, cause the computer to carry out any of the described decoding embodiments or variants.

[0017] These and other aspects, features and advantages of the general aspects will become apparent from the following detailed description of exemplary embodiments, which is to be read in connection with the accompanying drawings.

[0018] BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 illustrates a concept of resampling (RPR) step for inter prediction in an encoder.

[0019] Figure 2 illustrates an example resampling (RPR) step for inter prediction in a decoder.

[0020] Figure 3 illustrates an example of picture resolution change with use of RPR for inter prediction.

[0021] Figure 4 illustrates examples of RD curves anchor vs RPR.

[0022] Figure 5 illustrates an example neural network (NN) workflow for subsampling decision and downscaling prediction.

[0023] Figure 6 illustrates an example of a learning process.

[0024] Figure 7 illustrates an example neural network workflow for subsampling decision and downscaling ratio interpolation.

[0025] Figure 8 illustrates one embodiment of a method for encoding based on the general aspects described.

[0026] Figure 9 illustrates one embodiment of a method for decoding based on the general aspects described.

[0027] Figure 10 illustrates one embodiment of an apparatus for implementing encoding and / or decoding using the general aspects described.

[0028] Figure 11 illustrates a standard, generic, video compression scheme.

[0029] Figure 12 illustrates a standard, generic, video decompression scheme.

[0030] Figure 13 illustrates a processor-based system for encoding / decoding under the general described aspects.

[0031] DETAILED DESCRIPTION The embodiments described here are in the field of video compression and generally relate to video compression and video encoding and decoding more specifically to a method or an apparatus for downscaling ratio prediction for reference picture resampling (RPR).

[0032] To achieve high compression efficiency, image and video coding schemes usually employ block-based prediction, including motion vector 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 frame 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.

[0033] In the HEVC (High Efficiency Video Coding) video compression standard, motion compensated temporal prediction is employed to exploit the redundancy that exists between successive pictures of a video.

[0034] To do, a motion vector is associated to each prediction unit (PU). Each CTU (Coding Tree Unit) is represented by a Coding Tree in the compressed domain. This is a quad-tree division of the CTU, where each leaf is called a Coding Unit (CU).

[0035] Each CU is then given some Intra or Inter prediction parameters (Prediction Info). To do so, it is spatially partitioned into one or more Prediction Units (PUs), each PU being assigned some prediction information. The Intra or Inter coding mode is assigned on the CU level.

[0036] In the Versatile Video Coding (WC) / H.266 standard, the picture-based rescaling feature is named Reference Picture Resampling (RPR). Given an original video sequence composed of pictures of size (width x height), the encoder may choose for each frame which resolution (picture size) to use for coding the frame. Different picture parameter sets (PPS) are coded in the bit-stream with the possible sizes of the pictures and the slice / picture header indicates which PPS to use to decode the current video coding layer (VCL) network abstraction layer (NAL) unit.

[0037] The down-sampler (440) in Figure 1 and the up-sampler functions (540) in Figure 2 used as pre- or post-processing respectively are not specified by the standard.

[0038] For each frame, the encoder chooses whether to encode at original or downsized resolution (ex: picture width / height divided by 2). The choice can be made with two passes encoding or considering spatial and temporal activity in the original pictures, for example. Consequently, the decoded picture buffer (380) can contain pictures with different size as the current picture size.

[0039] In case one reference picture in the DPB has size different from the current picture, the re-scaling (430 / 530) (up-scale or down-scale) of the reference block to build the prediction block is made implicitly during the motion compensation process.

[0040] Figure 3 illustrates the application of RPR in a coded stream with successive pictures having different picture resolutions. This feature is for instance useful for adaptive streaming, to adapt the bitrate to the network constraints. Even if this is not normatively said, the downsampled pictures, that are not at the resolution indicated in the HLS, need to be resampled to show all decoded pictures on the end-display at a same (display or target) resolution, as illustrated in Figure 2 (540).

[0041] Along with downscaling, a QP offset may be applied when encoding the downsampled picture, typically a negative QP offset of -6 is applied when encoding a picture downsampled by 2.

[0042] Rate-distortion and complexity are two criteria that are usually used to compare video codecs performance.

[0043] Rate-distortion measures the compression efficiency, it gives the relationship between the bitrate (Equation 1) and the quality of the reconstructed video. Peak Signal to Noise Ratio (PSNR) (Equation 2) is often used to evaluate the quality metric.

[0044] Generally, a tradeoff between the bitrate and the distortion is controlled by a quantization parameter (QP) input. Video codec performance is evaluated by performing the bitrate and PSNR measurement at several QPs values, constituting then the rate distortion curve (RD-curve).

[0045] Traditionally, if one wants to compare the performance of two versions of the same video encoder for a range of QP, Bjontegaard delta rate (BD-rate) measurement is used to measure the average bitrate and the quality difference between RD-curve (Figure 4) of each version of the encoder.

[0046] An RPR encoder may re-scale input pictures before encoding. In the case of RPR vs non-RPR encoder version, BD-rate gain is usually reached for high QP values when both RD curves version are crossing as shown in Figure 4. Notice that the crossing point also known as a QP switch is video content dependent. It does not have the same value and can be different from frame to frame or from a group of frames to another. Estimated QP switch could be used as a value from which can be decided whether or not to apply the subsampling mode.

[0047] One option is to let the RDO (Rate distortion optimization) in the encoder decide when to apply subsampling mode. But this requires N+1 passes encoding, one for encoding a full resolution image and the N other passes for each downscaled ratio(s). This option presents the drawback of putting additional complexity at the encoder in terms of encoding time, and in general that is what one would like to avoid.

[0048] Another option, presented in a prior approach, is to train a neural network predictor in order to predict the QP switch related to the image content and then decide whether or not to apply RPR.

[0049] The embodiments described herein focus on adapting the downscaling resolution according to the input QP when downscaling decision is activated for Reference Picture Resampling. The goal is to improve the video compression efficiency in terms of bitrate reduction while maintaining the video quality, or equivalently to improve the quality while maintaining the bitrate.

[0050] The invention presented in the prior approach deals with features extracted from images to infer the decision whether or not to apply the downscaling resolution when Reference Picture Resampling is activated. The embodiments described herein introduce a method that calculates the optimal downscaling ratio and the quantization parameter switch for subsampling decisions.

[0051] The main embodiments of the aspects herein are as follows.

[0052] The first embodiment introduces Neural Network training and inference of a model estimating the downscaling ratio, quantization parameter offset, and quantization parameter switch for Reference Picture Resampling.

[0053] The second embodiment presents an interpolation method to calculate a downsampling ratio according to the quantization parameter input when the subsampling decision is activated for Reference Picture Resampling.

[0054] Embodiment-1 - Downscaling ratio and QP switch prediction for Reference Picture Resampling:

[0055] In this embodiment, subsampling decision for RPR mode is performed relying on a fully connected neural network prediction. All of the process of features extraction and preprocessing from a prior approach is summarized in Figure 5. The neural network is trained to predict (output) a QP switch value, QP offset value and a downscaling ratio value in view to decide whether to down sample the input image or not to get better encoding performances.

[0056] A large dataset of images is used to train the fully connected (FC) neural network (Figure 6). For each image, features are extracted and formatted. As an example, they are composed of Histogram of Oriented Gradient (HOG), Discrete Cosine Transform (DOT) coefficients and Down-up PSNR. Additionally, quantization input parameter is used to train the fully connected neural network. For that purpose, Mean Square Error (MSE) or Mean Absolute Error (MAE) loss is computed to ensure the convergence of the training model (Equation (3)).

[0057] Subsampling decision for RPR, downscaling ratio and QP offset sent to the encoder are derived as follows (Equations (4), (5) and (6)):

[0058] Embodiment-2 - Downscaling ratio inference and QP switch prediction for Reference Picture Resampling:

[0059] This embodiment introduces an interpolation method to calculate the optimal downscaling ratio given by an input QP and QP switch value inferred by a predictor. In this embodiment the fully connected Neural Network and Subsampling Decision for RPR have changed compared to the previous embodiment:

[0060] - “FC Neural Network” outputs only “QP switch”

[0061] - “Subsampling Decision for RPR” has as input only “QP switch” and will interpolate the “Downscaling ratio” A Fully connected neural network is trained to predict a QP switch value for a unique downscaling ratio. For instance, training samples are composed of concatenated features, namely, Histogram of Oriented Gradient (HOG), Discrete Cosine Transform (DOT) coefficients and Down-up PSNR. Then, a method for interpolating the downscaling ratio according to the QP input value is performed as a post-processing and can be, for instance, achieved inside the subsampling decision module Figure 7. A linear interpolation is given as an example in Equation (7) and (7bis), it could be a nonlinear one. ratiointerpoiated

[0062] Where: ratio interpolated G [ratiOmin.. ratiOmax] and QP G [QPswitch.. QPmax]

[0063] (7) can be also expressed as follows:

[0064] Subsampling decision for RPR, downscaling ration and QP offset sent to the encoder are defined as follows (Equations (8), (9) and (10)):

[0065] , . . (0, if QP < QP switch

[0066] Subsamplinq decision = 1 (8)

[0067] ( 1, otherwise

[0068] 1, if QP < QP switch

[0069] Downscalingratioratiointerpolated, otherwise (9)

[0070] „ „ ( QP_offset, if Subsampiinq decision = 1

[0071] QP_offset_output = ,

[0072] "r( Input QnPDoffff, set, otherwise (10)

[0073] One embodiment of a method 800 under the general aspects described here is shown in Figure 8. The method commences at start block 801 and control proceeds to block 810 for extracting features from a video sequence. Control proceeds from block 810 to block 820 fortraining a fully connected neural network using the extracted features to produce a quantization parameter switch point and quantization parameter offset. Control proceeds from block 820 to block 830 for determining a subsampling decision for reference picture resampling mode based on the quantization parameter switch point and quantization parameter offset. Control proceeds from block 830 to block 840 for encoding the video sequence in reference picture resampling mode using the subsampling decision.

[0074] One embodiment of a method 900 under the general aspects described here is shown in Figure 9. The method commences at start block 901 and control proceeds to block 910 for parsing video data from a video sequence for information indicative of picture size of a picture. Control proceeds from block 910 to block 920 for determining a resampling ratio if said information indicates said picture has been resampled. Control proceeds from block 920 to block 930 for decoding the video sequence in reference picture resampling mode using the picture size, a quantization parameter switch point and quantization parameter offset.

[0075] Figure 10 shows one embodiment of an apparatus 1000 for encoding, decoding, compressing or decompressing, or filtering of video data using the aforementioned methods. The apparatus comprises Processor 1010 and can be interconnected to a memory 1020 through at least one port. Both Processor 1010 and memory 1020 can also have one or more additional interconnections to external connections.

[0076] Processor 1010 is also configured to either insert or receive information in a bitstream and, either compressing, encoding, or decoding using any of the described aspects.

[0077] The embodiments described here include 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.

[0078] The aspects described and contemplated in this application can be implemented in many different forms. Figures 11 , 12, and 13 provide some embodiments, but other embodiments are contemplated and the discussion of Figures 11 , 12, and 13 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.

[0079] In the present application, the terms “reconstructed” and “decoded” may be used interchangeably, the terms “pixel” and “sample” may be used interchangeably, 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.

[0080] 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.

[0081] Various methods and other aspects described in this application can be used to modify modules, for example, the intra prediction, entropy coding, and / or decoding modules (160, 260, 145, 230), of a video encoder 100 and decoder 200 as shown in Figure 11 and Figure 12. Moreover, the present aspects are not limited to WC 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 WC and HEVC). Unless indicated otherwise, or technically precluded, the aspects described in this application can be used individually or in combination.

[0082] 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.

[0083] Figure 11 illustrates an encoder 100. Variations of this encoder 100 are contemplated, but the encoder 100 is described below for purposes of clarity without describing all expected variations.

[0084] Before being encoded, the video sequence may go through pre-encoding processing (101), 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.

[0085] In the encoder 100, a picture is encoded by the encoder elements as described below. The picture to be encoded is partitioned (102) and processed in units of, for example, CUs. 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 (160). In an inter mode, motion estimation (175) and compensation (170) are performed. The encoder decides (105) 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 (110) the predicted block from the original image block.

[0086] The prediction residuals are then transformed (125) and quantized (130). The quantized transform coefficients, as well as motion vectors and other syntax elements, are entropy coded (145) 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.

[0087] The encoder decodes an encoded block to provide a reference for further predictions. The quantized transform coefficients are de-quantized (140) and inverse transformed (150) to decode prediction residuals. Combining (155) the decoded prediction residuals and the predicted block, an image block is reconstructed. In-loop filters (165) are applied to the reconstructed picture to perform, for example, deblocking / SAO (Sample Adaptive Offset) filtering to reduce encoding artifacts. The filtered image is stored at a reference picture buffer (180).

[0088] Figure 12 illustrates a block diagram of a video decoder 200. In the decoder 200, a bitstream is decoded by the decoder elements as described below. Video decoder 200 generally performs a decoding pass reciprocal to the encoding pass as described in Figure 11. The encoder 100 also generally performs video decoding as part of encoding video data.

[0089] In particular, the input of the decoder includes a video bitstream, which can be generated by video encoder 100. The bitstream is first entropy decoded (230) to obtain transform coefficients, motion vectors, and other coded information. The picture partition information indicates how the picture is partitioned. The decoder may therefore divide (235) the picture according to the decoded picture partitioning information. The transform coefficients are de-quantized (240) and inverse transformed (250) to decode the prediction residuals. Combining (255) the decoded prediction residuals and the predicted block, an image block is reconstructed. The predicted block can be obtained (270) from intra prediction (260) or motion- compensated prediction (i.e. , inter prediction) (275). In-loop filters (265) are applied to the reconstructed image. The filtered image is stored at a reference picture buffer (280).

[0090] The decoded picture can further go through post-decoding processing (285), 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 (101). The post-decoding processing can use metadata derived in the pre-encoding processing and signaled in the bitstream.

[0091] Figure 13 illustrates a block diagram of an example of a system in which various aspects and embodiments are implemented. System 1000 can 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 document. 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 1000, singly or in combination, can be embodied in a single integrated circuit (IC), multiple ICs, and / or discrete components. For example, in at least one embodiment, the processing and encoder / decoder elements of system 1000 are distributed across multiple ICs and / or discrete components. In various embodiments, the system 1000 is communicatively coupled to one or more other systems, or other electronic devices, via, for example, a communications bus or through dedicated input and / or output ports. In various embodiments, the system 1000 is configured to implement one or more of the aspects described in this document.

[0092] The system 1000 includes at least one processor 1010 configured to execute instructions loaded therein for implementing, for example, the various aspects described in this document. Processor 1010 can include embedded memory, input output interface, and various other circuitries as known in the art. The system 1000 includes at least one memory 1020 (e.g., a volatile memory device, and / or a nonvolatile memory device). System 1000 includes a storage device 1040, which can include non-volatile memory and / or volatile memory, including, but not limited to, Electrically Erasable Programmable Read-Only Memory (EEPROM), Read-Only Memory (ROM), Programmable Read-Only Memory (PROM), Random Access Memory (RAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), flash, magnetic disk drive, and / or optical disk drive. The storage device 1040 can include an internal storage device, an attached storage device (including detachable and non-detachable storage devices), and / or a network accessible storage device, as non-limiting examples.

[0093] System 1000 includes an encoder / decoder module 1030 configured, for example, to process data to provide an encoded video or decoded video, and the encoder / decoder module 1030 can include its own processor and memory. The encoder / decoder module 1030 represents module(s) that can be included in a device to perform the encoding and / or decoding functions. As is known, a device can include one or both of the encoding and decoding modules. Additionally, encoder / decoder module 1030 can be implemented as a separate element of system 1000 or can be incorporated within processor 1010 as a combination of hardware and software as known to those skilled in the art.

[0094] Program code to be loaded onto processor 1010 or encoder / decoder 1030 to perform the various aspects described in this document can be stored in storage device 1040 and subsequently loaded onto memory 1020 for execution by processor 1010. In accordance with various embodiments, one or more of processor 1010, memory 1020, storage device 1040, and encoder / decoder module 1030 can store one or more of various items during the performance of the processes described in this document. Such stored items can 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.

[0095] In some embodiments, memory inside of the processor 1010 and / or the encoder / decoder module 1030 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 can be either the processor 1010 or the encoder / decoder module 1030) is used for one or more of these functions. The external memory can be the memory 1020 and / or the storage device 1040, 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, for example, 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).

[0096] The input to the elements of system 1000 can be provided through various input devices as indicated in block 1130. 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 Figure 13, include composite video.

[0097] In various embodiments, the input devices of block 1130 have associated respective input processing elements as known in the art. For example, the RF portion can 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) downconverting the selected signal, (iii) band-limiting again to a narrower band of frequencies to select (for example) a signal frequency band which can be referred to as a channel in certain embodiments, (iv) demodulating the downconverted and bandlimited 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 can include a tuner that performs various of these functions, including, for example, downconverting 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, downconverting, 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 can include inserting elements in between existing elements, such as, for example, inserting amplifiers and an analog-to-digital converter. In various embodiments, the RF portion includes an antenna.

[0098] Additionally, the USB and / or HDMI terminals can include respective interface processors for connecting system 1000 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, can be implemented, for example, within a separate input processing IC or within processor 1010 as necessary. Similarly, aspects of USB or HDMI interface processing can be implemented within separate interface les or within processor 1010 as necessary. The demodulated, error corrected, and demultiplexed stream is provided to various processing elements, including, for example, processor 1010, and encoder / decoder 1030 operating in combination with the memory and storage elements to process the datastream as necessary for presentation on an output device.

[0099] Various elements of system 1000 can be provided within an integrated housing, Within the integrated housing, the various elements can be interconnected and transmit data therebetween using suitable connection arrangement, for example, an internal bus as known in the art, including the Inter-IC (I2C) bus, wiring, and printed circuit boards.

[0100] The system 1000 includes communication interface 1050 that enables communication with other devices via communication channel 1060. The communication interface 1050 can include, but is not limited to, a transceiver configured to transmit and to receive data over communication channel 1060. The communication interface 1050 can include, but is not limited to, a modem or network card and the communication channel 1060 can be implemented, for example, within a wired and / or a wireless medium.

[0101] Data is streamed, or otherwise provided, to the system 1000, in various embodiments, using a wireless network such as a Wi-Fi network, for example IEEE 802.11 (IEEE refers to the Institute of Electrical and Electronics Engineers). The WiFi signal of these embodiments is received over the communications channel 1060 and the communications interface 1050 which are adapted for Wi-Fi communications. The communications channel 1060 of these embodiments is typically connected to an access point or router that provides access to external networks including the Internet for allowing streaming applications and other over-the-top communications. Other embodiments provide streamed data to the system 1000 using a set-top box that delivers the data over the HDMI connection of the input block 1130. Still other embodiments provide streamed data to the system 1000 using the RF connection of the input block 1130. As indicated above, various embodiments provide data in a nonstreaming manner. Additionally, various embodiments use wireless networks other than Wi-Fi, for example a cellular network or a Bluetooth network.

[0102] The system 1000 can provide an output signal to various output devices, including a display 1100, speakers 1110, and other peripheral devices 1120. The display 1100 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 1100 can be for a television, a tablet, a laptop, a cell phone (mobile phone), or another device. The display 1100 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 1120 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 1120 that provide a function based on the output of the system 1000. For example, a disk player performs the function of playing the output of the system 1000.

[0103] In various embodiments, control signals are communicated between the system 1000 and the display 1100, speakers 1110, or other peripheral devices 1120 using signaling such as AV.Link, Consumer Electronics Control (CEC), or other communications protocols that enable device-to-device control with or without user intervention. The output devices can be communicatively coupled to system 1000 via dedicated connections through respective interfaces 1070, 1080, and 1090. Alternatively, the output devices can be connected to system 1000 using the communications channel 1060 via the communications interface 1050. The display 1100 and speakers 1110 can be integrated in a single unit with the other components of system 1000 in an electronic device such as, for example, a television. In various embodiments, the display interface 1070 includes a display driver, such as, for example, a timing controller (T Con) chip. The display 1100 and speaker 1110 can alternatively be separate from one or more of the other components, for example, if the RF portion of input 1130 is part of a separate set-top box. In various embodiments in which the display 1100 and speakers 1110 are external components, the output signal can be provided via dedicated output connections, including, for example, HDMI ports, USB ports, or COMP outputs.

[0104] The embodiments can be carried out by computer software implemented by the processor 1010 or by hardware, or by a combination of hardware and software. As a non-limiting example, the embodiments can be implemented by one or more integrated circuits. The memory 1020 can be of any type appropriate to the technical environment and can be implemented using any appropriate data storage technology, such as optical memory devices, magnetic memory devices, semiconductor-based memory devices, fixed memory, and removable memory, as non-limiting examples. The processor 1010 can be of any type appropriate to the technical environment, and can encompass one or more of microprocessors, general purpose computers, special purpose computers, and processors based on a multi-core architecture, as nonlimiting examples.

[0105] 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 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.

[0106] 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. 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.

[0107] 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 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.

[0108] 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.

[0109] Note that the syntax elements as used herein are descriptive terms. As such, they do not preclude the use of other syntax element names.

[0110] 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.

[0111] Various embodiments may refer to parametric models or 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. It can be measured through a Rate Distortion Optimization (RDO) metric, or through Least Mean Square (LMS), Mean of Absolute Errors (MAE), or other such measurements. 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.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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 transforms, coding modes or flags. In this way, in an embodiment the same transform, parameter, or mode 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.

[0119] 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.

[0120] The preceding sections describe a number of embodiments, across various claim categories and types. Features of these embodiments can be provided alone or in any combination. Further, embodiments can include one or more of the following features, devices, or aspects, alone or in any combination, across various claim categories and types:

[0121] At least one embodiment comprises prediction of a downsampling ratio for reference picture resampling in an encoding or decoding process.

[0122] At least one embodiment comprises the aforementioned embodiments wherein a fully connected neural network is used for the prediction.

[0123] At least one embodiment comprises any of the aforementioned embodiments wherein extracted features from a video sequence are used to train the fully connected neural network.

[0124] At least one embodiment comprises any of the above embodiments wherein the extracted features comprise histogram of gradients, discrete cosine transform coefficients, and down-up PSNR.

[0125] At least one embodiment comprises any encoding or decoding operation based on the above operations.

[0126] At least one embodiment comprises performing encoding or decoding with the aforementioned methods on a sub-block.

[0127] At least one embodiment comprises a bitstream or signal that includes one or more of the described syntax elements, or variations thereof. At least one embodiment comprises a bitstream or signal that includes syntax conveying information generated according to any of the embodiments described.

[0128] At least one embodiment comprises creating and / or transmitting and / or receiving and / or decoding according to any of the embodiments described.

[0129] At least one embodiment comprises a method, process, apparatus, medium storing instructions, medium storing data, or signal according to any of the embodiments described.

[0130] At least one embodiment comprises inserting in the signaling syntax elements that enable the decoder to determine decoding information in a manner corresponding to that used by an encoder.

[0131] At least one embodiment comprises creating and / or transmitting and / or receiving and / or decoding a bitstream or signal that includes one or more of the described syntax elements, or variations thereof.

[0132] At least one embodiment comprises a TV, set-top box, cell phone, tablet, or other electronic device that performs transform method(s) according to any of the embodiments described.

[0133] At least one embodiment comprises a TV, set-top box, cell phone, tablet, or other electronic device that performs transform method(s) determination according to any of the embodiments described, and that displays (e.g., using a monitor, screen, or other type of display) a resulting image.

[0134] At least one embodiment comprises a TV, set-top box, cell phone, tablet, or other electronic device that selects, bandlimits, or tunes (e.g., using a tuner) a channel to receive a signal including an encoded image, and performs transform method(s) according to any of the embodiments described.

[0135] At least one embodiment comprises a TV, set-top box, cell phone, tablet, or other electronic device that receives (e.g., using an antenna) a signal over the air that includes an encoded image, and performs transform method(s).

Claims

CLAIMS1. A method, comprising: extracting features from a video sequence; training a fully connected neural network using the extracted features to produce a quantization parameter switch point and quantization parameter offset; determining a subsampling decision for reference picture resampling mode based on the quantization parameter switch point and quantization parameter offset; and, encoding the video sequence in reference picture resampling mode using the subsampling decision.

2. An apparatus, comprising: a memory, and a processor, configured to: extract features from a video sequence; train a fully connected neural network using the extracted features to produce a quantization parameter switch point and quantization parameter offset; determine a subsampling decision for reference picture resampling mode based on the quantization parameter switch point and quantization parameter offset; and, encode the video sequence in reference picture resampling mode using the subsampling decision.

3. A method, comprising: parsing video data from a video sequence for information indicative of picture size of a picture; determining a resampling ratio when said information indicates said picture has been resampled; and, decoding the video sequence in reference picture resampling mode using the picture size, the resampling ratio and said information comprising atleast one of a quantization parameter switch point and quantization parameter offset.

4. An apparatus, comprising: a memory, and a processor, configured to: parse video data from a video sequence for information indicative of picture size of a picture; determine a resampling ratio if said information indicates said picture has been resampled; and, decode the video sequence in reference picture resampling mode using the picture size, the resampling ratio and said information comprising at least one of a quantization parameter switch point and quantization parameter offset.

5. The method of Claim 1 , or the apparatus of Claim 2, wherein said training of the fully connected neural network comprises using quantization input parameters.

6. The method of any one of Claims 1 or 5, or the apparatus of any one of Claims 2 or 5, wherein said extracted features comprise histogram of gradients, Discrete Cosine Transforms coefficients, and down-up PSNR.

7. The method of any one of Claims 1 , 5, or 6, or the apparatus of any one of Claims 2, 5, or 6, wherein said subsampling decision comprises a downsampling ratio, a subsampling decision and a quantization parameter offset information.

8. The method of any one of Claims 1 , 5, 6, or 7, or the apparatus of any one of Claims 2, 5, 6, or 7, wherein a downscaling ratio is determined using interpolation.

9. The method or apparatus of Claim 8, wherein a downscaling ratio is inferred by prediction.

10. A device comprising: an apparatus according to Claim 4; and at least one of (i) an antenna configured to receive a signal, the signal including a video block, (ii) a band limiter configured to limit the received signal to a band of frequencies that includes a video block, and (iii) a display configured to display an output representative of a video block.

11. A non-transitory computer readable medium containing data content generated according to the method of any one of claims 1 , or 5 through 9, or by the apparatus of any one of claims 2, or 5 through 9, for playback using a processor.

12. A signal comprising video data generated according to the method of any one of claims 1 , or 5 through 9, or by the apparatus of any one of claims 2, or 5 through 9, for playback using a processor.

13. A computer program product comprising instructions which, when the program is executed by a computer, cause the computer to carry out the method of any one of claims 1 , or 3 or 5 through 9.

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