CN110944180B

CN110944180B - Chroma block prediction method and device

Info

Publication number: CN110944180B
Application number: CN201811210441.9A
Authority: CN
Inventors: 马祥; 牟凡; 杨海涛
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2018-09-21
Filing date: 2018-10-17
Publication date: 2023-04-28
Anticipated expiration: 2038-10-17
Also published as: CN110944180A

Abstract

The embodiment of the invention provides a method and a device for predicting a chroma block. The method obtains the average value of the brightness points in the brightness block template, then divides the template brightness points into two sets according to the average value, and the corresponding template chromaticity points are also divided into two sets. And respectively calculating the luminance mean value and the chrominance mean value in each set, and deriving a linear model coefficient based on the two luminance mean values and the corresponding chrominance mean value. And then obtaining the predicted value of the chromaticity point of the chromaticity block according to the value of the brightness point of the brightness block and the linear model coefficient. The embodiment of the invention can reduce the complexity of the linear model and improve the robustness, thereby improving the efficiency of chroma coding and decoding.

Description

Chroma block prediction method and device

Technical Field

The present application relates to the field of video encoding and decoding, and more particularly, to a chrominance block prediction method and apparatus.

Background

With the rapid development of internet technology and the increasing abundance of physical and mental culture of people, the application requirements for videos in the internet, especially for high-definition videos, are increasing, the data volume of the high-definition videos is very large, and the problem that the high-definition videos must be firstly solved in order to be transmitted in the internet with limited bandwidth is the problem of video encoding and decoding. Video codecs are widely used in digital video applications such as broadcast digital television, video distribution over the internet and mobile networks, real-time conversational applications such as video chat and video conferencing, DVD and blu-ray discs, video content acquisition and editing systems, and security applications for camcorders.

Each picture of a video sequence is typically partitioned into non-overlapping sets of blocks, typically encoded at the block level. For example, the prediction block is generated by spatial (intra-picture) prediction and temporal (inter-picture) prediction. Accordingly, the prediction modes may include intra prediction modes (spatial prediction) and inter prediction modes (temporal prediction). Wherein the set of intra prediction modes may include 35 different intra prediction modes, for example, a non-directional mode such as a DC (or mean) mode and a planar mode; or a directivity pattern as defined in h.265; or 67 different intra prediction modes, for example, a non-directional mode such as a DC (or mean) mode and a plane mode; or a directivity pattern as defined in h.266 under development. The set of inter prediction modes depends on the available reference pictures and other inter prediction parameters, e.g. on whether the entire reference picture is used or only a part of the reference picture is used.

Existing video is typically color video, which contains a chrominance component in addition to a luminance component. Therefore, in addition to encoding the luminance component, it is also necessary to encode the chrominance component. In the prior art, during intra prediction, the value of the chrominance component can be obtained through a relatively complex method, and the efficiency of chrominance coding and decoding is low.

Disclosure of Invention

Embodiments of the present application (or the present disclosure) provide apparatus and methods for chroma block prediction.

In a first aspect, the present invention relates to a method of prediction of a chroma block. The method is performed by a device that decodes a video stream or a device that encodes a video stream. The method comprises the following steps: obtaining the average value of brightness points in a brightness block template, wherein the brightness block corresponds to the chromaticity block; dividing the brightness points in the brightness block template into two brightness sets, wherein the value of the brightness points in the first brightness set is smaller than the average value of the brightness points in the brightness block template, and the value of the brightness points in the second brightness set is larger than the average value of the brightness points in the brightness block template. Then, according to the value of the brightness point in the first brightness set, a first brightness average value is obtained; and obtaining a first chrominance mean value according to the value of the chrominance point corresponding to the luminance point in the first luminance set. Obtaining a second brightness average value according to the value of the brightness point in the second brightness set; and obtaining a second chromaticity mean value according to the value of the chromaticity point corresponding to the brightness point in the second brightness set. The method further comprises obtaining a first set of linear model coefficients according to the first luminance average and the first chrominance average, and the second luminance average and the second chrominance average; and obtaining a predicted value of a chromaticity point of the chromaticity block according to the value of the brightness point of the brightness block and the first group of linear model coefficients.

Compared with the method for obtaining the linear model coefficient based on the least square method in the prior art, the method for obtaining the linear model coefficient based on the least square method can reduce complexity of the linear model; compared with the prior art that linear model coefficients are obtained based on an extremum method, the embodiment of the invention can improve robustness, so that the embodiment of the invention can improve the efficiency of chroma encoding and decoding.

In one embodiment, the linear model coefficient β is

β＝C _mean -α*L _mean ，

Wherein the average value of the brightness points in the brightness block template is L _mean The average value of the chroma points in the chroma block template is C _mean 。

Compared with the method for obtaining the linear model coefficient based on the least square method in the prior art, the method for obtaining the linear model coefficient based on the least square method can reduce complexity of the linear model; compared with the prior art that the linear model coefficient is obtained based on the extremum method, the method and the device can improve the accuracy of calculation.

In a second aspect, the present invention is directed to an apparatus for decoding a video stream, comprising a processor and a memory. The memory stores instructions that cause the processor to perform the method according to the first aspect.

In a third aspect, the invention relates to an apparatus for encoding a video stream, comprising a processor and a memory. The memory stores instructions that cause the processor to perform the method according to the first aspect.

In a fourth aspect, a computer-readable storage medium having instructions stored thereon that, when executed, cause one or more processors to encode video data is presented. The instructions cause the one or more processors to perform the method according to any possible embodiment of the first aspect.

In a fifth aspect, the invention relates to a computer program comprising a program code for performing the method according to any of the possible embodiments of the first aspect when run on a computer.

The details of one or more embodiments are set forth in the accompanying drawings and the description below. Other features, objects, and advantages will be apparent from the description and drawings, and from the claims.

Drawings

In order to more clearly describe the technical solutions in the embodiments or the background of the present application, the following description will describe the drawings that are required to be used in the embodiments or the background of the present application.

FIG. 1A shows a block diagram of an example video coding system for implementing an embodiment of the invention;

fig. 1B shows a block diagram of an example video encoding system incorporating either or both of encoder 20 of fig. 2 and decoder 30 of fig. 3;

FIG. 2 shows a block diagram of an example architecture of a video encoder for implementing an embodiment of the invention;

FIG. 3 shows a block diagram of an example architecture of a video decoder for implementing an embodiment of the invention;

FIG. 4 shows a block diagram of an example encoding or decoding device;

FIG. 5 shows a block diagram of another example encoding or decoding device;

FIG. 6 shows an example of a YUV format sampling grid;

FIG. 7 illustrates one embodiment of a cross-component prediction (Cross component prediction, CCP) mode;

FIG. 8 (a) shows a top and left template schematic;

FIG. 8 (b) shows another schematic of one cope and left mold plate;

FIG. 9 (a) shows a schematic of a multi-linear model (Multiple model linear model, MMLM for short) prediction mode usage template;

FIG. 9 (b) shows a schematic of a multidirectional Linear model (Multi-direction linear model, MDLM) prediction mode usage template;

FIG. 10 shows a flow chart of a method of a first embodiment of the invention;

FIG. 11 shows a schematic diagram of a linear model according to a first embodiment of the present invention;

FIG. 12 shows a flow chart of a method of a second embodiment of the invention;

FIG. 13 shows a schematic diagram of a linear model of a second embodiment of the invention;

FIG. 14 shows a schematic diagram of a third embodiment of the invention;

FIG. 15 shows a schematic diagram of a fourth embodiment of the invention; and

Fig. 16 shows a schematic diagram of a fifth embodiment of the present invention.

In the following, like reference numerals refer to like or at least functionally equivalent features, unless specifically noted otherwise.

Detailed Description

Video coding generally refers to processing a sequence of pictures that form a video or video sequence. In the field of video coding, the terms "picture", "frame" or "image" may be used as synonyms. Video encoding as used in this application (or this disclosure) refers to video encoding or video decoding. Video encoding is performed on the source side, typically including processing (e.g., by compression) the original video picture to reduce the amount of data required to represent the video picture, thereby more efficiently storing and/or transmitting. Video decoding is performed on the destination side, typically involving inverse processing with respect to the encoder to reconstruct the video pictures. The embodiment relates to video picture "encoding" is understood to relate to "encoding" or "decoding" of a video sequence. The combination of the encoding portion and the decoding portion is also called codec (encoding and decoding, or simply encoding).

There are two main methods for deriving Linear Model (LM) coefficients, one using least squares and one based on extremum. A method of deriving a linear model system using products of adjacent N reference pixels and corresponding chrominance pixels of a luminance block is called a least square method (simply referred to as a least square method). By maximum brightness value L _max Minimum brightness value L _min The corresponding value pair, a method for determining the linear model coefficients is called extremum method. The existing method based on least square method is high in complexity, and linear model is derived based on extremum methodThe method of coefficients is less robust. The embodiment of the invention provides an improved linear model coefficient deriving method and device.

Each picture of a video sequence is typically partitioned into non-overlapping sets of blocks, typically encoded at the block level. In other words, the encoder side typically processes, i.e. encodes, video at the block (also referred to as image block, or video block) level, e.g. generates a prediction block by spatial (intra-picture) prediction and temporal (inter-picture) prediction, subtracts the prediction block from the current block (currently processed or to-be-processed block) to obtain a residual block, transforms the residual block in the transform domain and quantizes the residual block to reduce the amount of data to be transmitted (compressed), while the decoder side applies the inverse processing part of the relative encoder to the encoded or compressed block to reconstruct the current block for representation. In addition, the encoder replicates the decoder processing loop so that the encoder and decoder generate the same predictions (e.g., intra-prediction and inter-prediction) and/or reconstructions for processing, i.e., encoding, the subsequent blocks.

The term "block" may be part of a picture or frame. The key terms are defined as follows:

current block: referring to the block currently being processed. For example, in encoding, refers to the block currently being encoded; in decoding, a block currently being decoded is referred to. If the currently processed block is a chroma component block, it is referred to as the current chroma block. The luminance block corresponding to the current chrominance block may be referred to as the current luminance block.

Reference block: refers to a block that provides a reference signal for the current block. During the search process, multiple reference blocks may be traversed to find the best reference block.

Prediction block: the block providing prediction for the current block is referred to as a prediction block. For example, after traversing multiple reference blocks, the best reference block is found, which will provide prediction for the current block, which is referred to as the prediction block.

Image block signal: pixel values or sampled signals within an image block.

Prediction signal: the pixel values or sampled signals within a prediction block are referred to as prediction signals.

Embodiments of encoder 20, decoder 30, and encoding system 10 are described below based on fig. 1A, 1B through 3.

Fig. 1A is a conceptual or schematic block diagram illustrating an exemplary encoding system 10, e.g., a video encoding system 10 that may utilize the techniques of this application (this disclosure). Encoder 20 (e.g., video encoder 20) and decoder 30 (e.g., video decoder 30) of video encoding system 10 represent examples of devices that may be used to perform intra-prediction according to the various examples described herein. As shown in fig. 1A, encoding system 10 includes a source device 12 for providing encoded data 13, e.g., encoded pictures 13, to a destination device 14, e.g., decoding encoded data 13.

Source device 12 includes an encoder 20, and may additionally optionally include a picture source 16, a preprocessing unit 18, such as picture preprocessing unit 18, and a communication interface or communication unit 22.

The picture source 16 may include or may be any type of picture capture device for capturing, for example, real world pictures, and/or any type of picture or comment (for screen content encoding, some text on the screen is also considered part of the picture or image to be encoded), for example, a computer graphics processor for generating computer animated pictures, or any type of device for capturing and/or providing real world pictures, computer animated pictures (e.g., screen content, virtual Reality (VR) pictures), and/or any combination thereof (e.g., real scene (augmented reality, AR) pictures).

A picture may be regarded as a two-dimensional array or matrix of sampling points with luminance values. The sampling points in the array may also be referred to as pixels (pixels) or pixels (pels). The number of sampling points of the array or picture in the horizontal and vertical directions (or axes) defines the size and/or resolution of the picture. To represent color, three color components are typically employed, i.e., a picture may be represented as or contain three sample arrays. In RBG format or color space, a picture includes corresponding red, green, and blue sample arrays. However, in video coding, each pixel is typically represented in a luminance/chrominance format or color space, e.g., YCbCr, including a luminance component indicated by Y (which may sometimes be indicated by L) and two chrominance components indicated by Cb and Cr. The luminance (luma) component Y represents the luminance or grayscale intensity (e.g., the same in a grayscale picture), while the two chrominance (chroma) components Cb and Cr represent the chrominance or color information components. Accordingly, a picture in YCbCr format includes a luma sample array of luma sample values (Y) and two chroma sample arrays of chroma values (Cb and Cr). Pictures in RGB format may be converted or transformed into YCbCr format and vice versa, a process also known as color transformation or conversion. If the picture is black, the picture may include only the luma sample array.

Picture source 16 (e.g., video source 16) may be, for example, a camera for capturing pictures, a memory such as a picture memory, a memory that includes or stores previously captured or generated pictures, and/or any type of (internal or external) interface that captures or receives pictures. The camera may be, for example, an integrated camera, either local or integrated in the source device, and the memory may be, for example, an integrated memory, either local or integrated in the source device. The interface may be, for example, an external interface that receives pictures from an external video source, such as an external picture capture device, like a camera, an external memory or an external picture generation device, such as an external computer graphics processor, a computer or a server. The interface may be any kind of interface according to any proprietary or standardized interface protocol, e.g. a wired or wireless interface, an optical interface. The interface to acquire the picture data 17 may be the same interface as the communication interface 22 or a part of the communication interface 22.

The picture or picture data 17 (e.g., video data 16) may also be referred to as an original picture or original picture data 17, as distinguished from the preprocessing unit 18 and the processing performed by the preprocessing unit 18.

The preprocessing unit 18 is for receiving (original) picture data 17 and performing preprocessing on the picture data 17 to obtain a preprocessed picture 19 or preprocessed picture data 19. For example, preprocessing performed by preprocessing unit 18 may include truing, color format conversion (e.g., from RGB to YCbCr), toning, or denoising. It is understood that the preprocessing unit 18 may be an optional component.

Encoder 20, e.g., video encoder 20, is operative to receive preprocessed picture data 19 and provide encoded picture data 21 (details are described further below, e.g., based on fig. 2 or fig. 4). In one example, encoder 20 may be used to perform embodiments one through seven described below.

The communication interface 22 of the source device 12 may be used to receive the encoded picture data 21 and transmit it to other devices, such as the destination device 14 or any other device, for storage or direct reconstruction, or for processing the encoded picture data 21 before storing the encoded data 13 and/or transmitting the encoded data 13 to the other devices, such as the destination device 14 or any other device for decoding or storage, respectively.

The destination device 14 includes a decoder 30 (e.g., a video decoder 30), and may additionally, i.e., alternatively, include a communication interface or unit 28, a post-processing unit 32, and a display device 34.

The communication interface 28 of the destination device 14 is for receiving the encoded picture data 21 or the encoded data 13, e.g. directly from the source device 12 or any other source, e.g. a storage device, e.g. an encoded picture data storage device.

Communication interface 22 and communication interface 28 may be used to transmit or receive encoded picture data 21 or encoded data 13 via a direct communication link between source device 12 and destination device 14, such as a direct wired or wireless connection, or via any type of network, such as a wired or wireless network or any combination thereof, or any type of private and public networks, or any combination thereof.

The communication interface 22 may, for example, be used to encapsulate the encoded picture data 21 into a suitable format, such as packets, for transmission over a communication link or communication network.

The communication interface 28 forming a corresponding part of the communication interface 22 may for example be used for unpacking the encoded data 13 to obtain the encoded picture data 21.

Both communication interface 22 and communication interface 28 may be configured as unidirectional communication interfaces, as indicated by the arrow from source device 12 to destination device 14 for encoded picture data 13 in fig. 1A, or as bi-directional communication interfaces, and may be used, for example, to send and receive messages to establish a connection, acknowledge and exchange any other information related to the communication link and/or data transmission, such as encoded picture data transmission.

Decoder 30 is used to receive encoded picture data 21 and provide decoded picture data 31 or decoded picture 31 (details will be described further below, e.g., based on fig. 3 or fig. 5). In one example, decoder 30 may be used to perform embodiments one through seven described below.

The post-processor 32 of the destination device 14 is used to post-process the decoded picture data 31 (also referred to as reconstructed slice data), e.g., the decoded picture 131, to obtain post-processed picture data 33, e.g., the post-processed picture 33. Post-processing performed by post-processing unit 32 may include, for example, color format conversion (e.g., conversion from YCbCr to RGB), toning, truing, or resampling, or any other processing for preparing decoded picture data 31 for display by display device 34, for example.

The display device 34 of the destination device 14 is for receiving the post-processed picture data 33 to display the picture to, for example, a user or viewer. The display device 34 may be or include any type of display for presenting reconstructed pictures, for example, an integrated or external display or monitor. For example, the display may include a liquid crystal display (liquid crystal display, LCD), an organic light emitting diode (organic light emitting diode, OLED) display, a plasma display, a projector, a micro LED display, a liquid crystal on silicon (liquid crystal on silicon, LCoS), a digital light processor (digital light processor, DLP), or any other type of display.

Although fig. 1A depicts source device 12 and destination device 14 as separate devices, device embodiments may also include the functionality of both source device 12 and destination device 14, or both, i.e., source device 12 or corresponding functionality and destination device 14 or corresponding functionality. In such embodiments, the source device 12 or corresponding functionality and the destination device 14 or corresponding functionality may be implemented using the same hardware and/or software, or using separate hardware and/or software, or any combination thereof.

It will be apparent to those skilled in the art from this description that the functionality of the different units or the existence and (exact) division of the functionality of the source device 12 and/or destination device 14 shown in fig. 1A may vary depending on the actual device and application.

Encoder 20 (e.g., video encoder 20) and decoder 30 (e.g., video decoder 30) may each be implemented as any of a variety of suitable circuits, such as one or more microprocessors, digital signal processors (digital signal processor, DSPs), application-specific integrated circuits (ASICs), field-programmable gate array, FPGA, discrete logic, hardware, or any combinations thereof. If the techniques are implemented in part in software, an apparatus may store instructions of the software in a suitable non-transitory computer-readable storage medium and may execute the instructions in hardware using one or more processors to perform the techniques of this disclosure. Any of the foregoing (including hardware, software, a combination of hardware and software, etc.) may be considered one or more processors. Each of video encoder 20 and video decoder 30 may be contained in one or more encoders or decoders, either of which may be integrated as part of a combined encoder/decoder (codec) in the corresponding device.

Source device 12 may be referred to as a video encoding device or video encoding apparatus. Destination device 14 may be referred to as a video decoding device or video decoding apparatus. The source device 12 and the destination device 14 may be examples of video encoding devices or video encoding apparatus.

Source device 12 and destination device 14 may comprise any of a variety of devices, including any type of handheld or stationary device, such as a notebook or laptop computer, mobile phone, smart phone, tablet or tablet computer, video camera, desktop computer, set-top box, television, display device, digital media player, video game console, video streaming device (e.g., content service server or content distribution server), broadcast receiver device, broadcast transmitter device, etc., and may not use or use any type of operating system.

In some cases, source device 12 and destination device 14 may be equipped for wireless communication. Thus, the source device 12 and the destination device 14 may be wireless communication devices.

In some cases, the video encoding system 10 shown in fig. 1A is merely an example, and the techniques of this disclosure may be applicable to video encoding settings (e.g., video encoding or video decoding) that do not necessarily involve any data communication between encoding and decoding devices. In other examples, the data may be retrieved from local memory, streamed over a network, and the like. The video encoding device may encode and store data to the memory and/or the video decoding device may retrieve and decode data from the memory. In some examples, encoding and decoding are performed by devices that do not communicate with each other, but instead only encode data to memory and/or retrieve data from memory and decode data.

It should be appreciated that for each of the examples described above with reference to video encoder 20, video decoder 30 may be used to perform the reverse process. Regarding signaling syntax elements, video decoder 30 may be configured to receive and parse such syntax elements and decode the associated video data accordingly. In some examples, video encoder 20 may entropy encode the syntax elements into an encoded video bitstream. In such examples, video decoder 30 may parse such syntax elements and decode the relevant video data accordingly.

Fig. 1B is an illustration of an example of a video encoding system 40 including encoder 20 of fig. 2 and/or decoder 30 of fig. 3, according to an example embodiment. The system 40 may implement a combination of the various techniques of the present application. In the illustrated embodiment, video encoding system 40 may include an imaging device 41, a video encoder 20, a video decoder 30 (and/or a video encoder implemented by logic circuitry 47 of a processing unit 46), an antenna 42, one or more processors 43, one or more memories 44, and/or a display device 45.

As shown, imaging device 41, antenna 42, processing unit 46, logic 47, video encoder 20, video decoder 30, processor 43, memory 44, and/or display device 45 are capable of communicating with each other. As discussed, although video encoding system 40 is depicted with video encoder 20 and video decoder 30, in different examples, video encoding system 40 may include only video encoder 20 or only video decoder 30.

In some examples, as shown, video encoding system 40 may include an antenna 42. For example, the antenna 42 may be used to transmit or receive an encoded bitstream of video data. Additionally, in some examples, video encoding system 40 may include a display device 45. The display device 45 may be used to present video data. In some examples, as shown, logic circuitry 47 may be implemented by processing unit 46. The processing unit 46 may comprise application-specific integrated circuit (ASIC) logic, a graphics processor, a general-purpose processor, or the like. The video encoding system 40 may also include an optional processor 43, which optional processor 43 may similarly include application-specific integrated circuit (ASIC) logic, a graphics processor, a general purpose processor, and the like. In some examples, logic 47 may be implemented in hardware, such as video encoding dedicated hardware, processor 43 may be implemented in general purpose software, an operating system, or the like. In addition, the memory 44 may be any type of memory, such as volatile memory (e.g., static random access memory (Static Random Access Memory, SRAM), dynamic random access memory (Dynamic Random Access Memory, DRAM), etc.) or non-volatile memory (e.g., flash memory, etc.), and the like. In a non-limiting example, the memory 44 may be implemented by an overspeed cache. In some examples, logic circuitry 47 may access memory 44 (e.g., for implementing an image buffer). In other examples, logic 47 and/or processing unit 46 may include memory (e.g., a cache, etc.) for implementing an image buffer, etc.

In some examples, video encoder 20 implemented by logic circuitry may include an image buffer (e.g., implemented by processing unit 46 or memory 44) and a graphics processing unit (e.g., implemented by processing unit 46). The graphics processing unit may be communicatively coupled to the image buffer. The graphics processing unit may include video encoder 20 implemented by logic circuitry 47 to implement the various modules discussed with reference to fig. 2 and/or any other encoder system or subsystem described herein. Logic circuitry may be used to perform various operations discussed herein.

Video decoder 30 may be implemented in a similar manner by logic circuit 47 to implement the various modules discussed with reference to decoder 30 of fig. 3 and/or any other decoder system or subsystem described herein. In some examples, video decoder 30 implemented by logic circuitry may include an image buffer (implemented by processing unit 2820 or memory 44) and a graphics processing unit (e.g., implemented by processing unit 46). The graphics processing unit may be communicatively coupled to the image buffer. The graphics processing unit may include video decoder 30 implemented by logic circuit 47 to implement the various modules discussed with reference to fig. 3 and/or any other decoder system or subsystem described herein.

In some examples, antenna 42 of video encoding system 40 may be used to receive an encoded bitstream of video data. As discussed, the encoded bitstream may include data related to the encoded video frame, indicators, index values, mode selection data, etc., discussed herein, such as data related to the encoded partitions (e.g., transform coefficients or quantized transform coefficients, optional indicators (as discussed), and/or data defining the encoded partitions). Video encoding system 40 may also include a video decoder 30 coupled to antenna 42 and used to decode the encoded bitstream. The display device 45 is used to present video frames.

Encoder & encoding method

Fig. 2 shows a schematic/conceptual block diagram of an example of a video encoder 20 for implementing the techniques of this application (disclosure). In the example of fig. 2, video encoder 20 includes residual calculation unit 204, transform processing unit 206, quantization unit 208, inverse quantization unit 210, inverse transform processing unit 212, reconstruction unit 214, buffer 216, loop filter unit 220, decoded picture buffer (decoded picture buffer, DPB) 230, prediction processing unit 260, and entropy encoding unit 270. The prediction processing unit 260 may include an inter prediction unit 244, an intra prediction unit 254, and a mode selection unit 262. The inter prediction unit 244 may include a motion estimation unit and a motion compensation unit (not shown). The video encoder 20 shown in fig. 2 may also be referred to as a hybrid video encoder or a video encoder according to a hybrid video codec.

For example, the residual calculation unit 204, the transform processing unit 206, the quantization unit 208, the prediction processing unit 260 and the entropy encoding unit 270 form a forward signal path of the encoder 20, whereas for example the inverse quantization unit 210, the inverse transform processing unit 212, the reconstruction unit 214, the buffer 216, the loop filter 220, the decoded picture buffer (decoded picture buffer, DPB) 230, the prediction processing unit 260 form a backward signal path of the encoder, wherein the backward signal path of the encoder corresponds to the signal path of the decoder (see decoder 30 in fig. 3).

Encoder 20 receives picture 201 or a block 203 of picture 201, e.g., a picture in a sequence of pictures forming a video or video sequence, through, e.g., input 202. The picture block 203 may also be referred to as a current picture block or a picture block to be encoded, and the picture 201 may be referred to as a current picture or a picture to be encoded (especially when distinguishing the current picture from other pictures in video encoding, such as previously encoded and/or decoded pictures in the same video sequence, i.e. a video sequence also comprising the current picture).

Segmentation

An embodiment of encoder 20 may comprise a partitioning unit (not shown in fig. 2) for partitioning picture 201 into a plurality of blocks, e.g. blocks 203, typically into a plurality of non-overlapping blocks. The segmentation unit may be used to use the same block size for all pictures in the video sequence and a corresponding grid defining the block size, or to alter the block size between pictures or subsets or groups of pictures and to segment each picture into corresponding blocks.

In one example, prediction processing unit 260 of video encoder 20 may be configured to perform any combination of the above-described partitioning techniques.

Like picture 201, block 203 is also or may be regarded as a two-dimensional array or matrix of sampling points with luminance values (sampling values), albeit of smaller size than picture 201. In other words, block 203 may include, for example, one sampling array (e.g., a luminance array in the case of black-and-white picture 201) or three sampling arrays (e.g., one luminance array and two chrominance arrays in the case of color pictures) or any other number and/or class of arrays depending on the color format applied. The number of sampling points in the horizontal and vertical directions (or axes) of the block 203 defines the size of the block 203.

The encoder 20 as shown in fig. 2 is used to encode a picture 201 block by block, e.g. perform encoding and prediction on each block 203.

Residual calculation

The residual calculation unit 204 is configured to calculate a residual block 205 based on the picture block 203 and the prediction block 265 (further details of the prediction block 265 are provided below), for example, by subtracting sample values of the prediction block 265 from sample values of the picture block 203 on a sample-by-sample (pixel-by-pixel) basis to obtain the residual block 205 in a sample domain.

Transformation

The transform processing unit 206 is configured to apply a transform, such as a discrete cosine transform (discrete cosine transform, DCT) or a discrete sine transform (discrete sine transform, DST), on the sample values of the residual block 205 to obtain transform coefficients 207 in the transform domain. The transform coefficients 207 may also be referred to as transform residual coefficients and represent the residual block 205 in the transform domain.

The transform processing unit 206 may be used to apply integer approximations of DCT/DST, such as the transforms specified for HEVC/H.265. Such integer approximations are typically scaled by some factor compared to the orthogonal DCT transform. To maintain the norms of the forward and inverse transformed processed residual blocks, an additional scaling factor is applied as part of the transformation process. The scaling factor is typically selected based on certain constraints, e.g., the scaling factor is a tradeoff between power of 2, bit depth of transform coefficients, accuracy, and implementation cost for shift operations, etc. For example, a specific scaling factor is specified for inverse transformation by, for example, the inverse transformation processing unit 212 on the decoder 30 side (and for corresponding inverse transformation by, for example, the inverse transformation processing unit 212 on the encoder 20 side), and accordingly, a corresponding scaling factor may be specified for positive transformation by the transformation processing unit 206 on the encoder 20 side.

Quantization

The quantization unit 208 is for quantizing the transform coefficients 207, for example by applying scalar quantization or vector quantization, to obtain quantized transform coefficients 209. The quantized transform coefficients 209 may also be referred to as quantized residual coefficients 209. The quantization process may reduce the bit depth associated with some or all of the transform coefficients 207. For example, n-bit transform coefficients may be rounded down to m-bit transform coefficients during quantization, where n is greater than m. The quantization level may be modified by adjusting quantization parameters (quantization parameter, QP). For example, for scalar quantization, different scales may be applied to achieve finer or coarser quantization. Smaller quantization step sizes correspond to finer quantization, while larger quantization step sizes correspond to coarser quantization. The appropriate quantization step size may be indicated by a quantization parameter (quantization parameter, QP). For example, the quantization parameter may be an index of a predefined set of suitable quantization steps. For example, smaller quantization parameters may correspond to fine quantization (smaller quantization step size) and larger quantization parameters may correspond to coarse quantization (larger quantization step size) and vice versa. Quantization may involve division by a quantization step size and corresponding quantization or inverse quantization, e.g., performed by inverse quantization 210, or may involve multiplication by a quantization step size. Embodiments according to some standards, such as HEVC, may use quantization parameters to determine quantization step sizes. In general, the quantization step size may be calculated based on quantization parameters using a fixed-point approximation of an equation that includes division. Additional scaling factors may be introduced for quantization and inverse quantization to recover norms of residual blocks that may be modified due to the scale used in the fixed point approximation of the equation for quantization step size and quantization parameters. In one example embodiment, the inverse transformed and inverse quantized scales may be combined. Alternatively, a custom quantization table may be used and signaled from the encoder to the decoder, e.g., in a bitstream. Quantization is a lossy operation, where the larger the quantization step size, the larger the loss.

The inverse quantization unit 210 is configured to apply inverse quantization of the quantization unit 208 on the quantized coefficients to obtain inverse quantized coefficients 211, e.g., apply an inverse quantization scheme of the quantization scheme applied by the quantization unit 208 based on or using the same quantization step size as the quantization unit 208. The dequantized coefficients 211 may also be referred to as dequantized residual coefficients 211, correspond to the transform coefficients 207, although the losses due to quantization are typically different from the transform coefficients.

The inverse transform processing unit 212 is configured to apply an inverse transform of the transform applied by the transform processing unit 206, for example, an inverse discrete cosine transform (discrete cosine transform, DCT) or an inverse discrete sine transform (discrete sine transform, DST), to obtain an inverse transform block 213 in the sample domain. The inverse transform block 213 may also be referred to as an inverse transformed inverse quantized block 213 or an inverse transformed residual block 213.

A reconstruction unit 214 (e.g., a summer 214) is used to add the inverse transform block 213 (i.e., the reconstructed residual block 213) to the prediction block 265 to obtain the reconstructed block 215 in the sample domain, e.g., to add sample values of the reconstructed residual block 213 to sample values of the prediction block 265.

Optionally, a buffer unit 216, e.g. a line buffer 216 (or simply "buffer" 216), is used to buffer or store the reconstructed block 215 and the corresponding sample values for e.g. intra prediction. In other embodiments, the encoder may be configured to use the unfiltered reconstructed block and/or the corresponding sample values stored in the buffer unit 216 for any kind of estimation and/or prediction, such as intra prediction.

For example, embodiments of encoder 20 may be configured such that buffer unit 216 is used not only to store reconstructed blocks 215 for intra prediction 254, but also for loop filter unit 220 (not shown in fig. 2), and/or such that buffer unit 216 and decoded picture buffer unit 230 form one buffer, for example. Other embodiments may be used to use the filtered block 221 and/or blocks or samples (neither shown in fig. 2) from the decoded picture buffer 230 as an input or basis for the intra prediction 254.

The loop filter unit 220 (or simply "loop filter" 220) is used to filter the reconstructed block 215 to obtain a filtered block 221, which facilitates pixel transitions or improves video quality. Loop filter unit 220 is intended to represent one or more loop filters, such as deblocking filters, sample-adaptive offset (SAO) filters, or other filters, such as bilateral filters, adaptive loop filters (adaptive loop filter, ALF), or sharpening or smoothing filters, or collaborative filters. Although loop filter unit 220 is shown in fig. 2 as an in-loop filter, in other configurations loop filter unit 220 may be implemented as a post-loop filter. The filtered block 221 may also be referred to as a filtered reconstructed block 221. Decoded picture buffer 230 may store the reconstructed encoded block after loop filter unit 220 performs a filtering operation on the reconstructed encoded block.

Embodiments of encoder 20 (and correspondingly loop filter unit 220) may be configured to output loop filter parameters (e.g., sample adaptive offset information), e.g., directly or after entropy encoding by entropy encoding unit 270 or any other entropy encoding unit, e.g., such that decoder 30 may receive and apply the same loop filter parameters for decoding.

Decoded picture buffer (decoded picture buffer, DPB) 230 may be a reference picture memory that stores reference picture data for use by video encoder 20 in encoding video data. DPB 230 may be formed of any of a variety of memory devices, such as dynamic random access memory (dynamic random access memory, DRAM) (including synchronous DRAM)

Synchronous DRAM (SDRAM), magnetoresistive RAM (MRAM), resistive RAM (RRAM), or other types of memory devices. DPB 230 and buffer 216 may be provided by the same memory device or separate memory devices. In a certain example, a decoded picture buffer (decoded picture buffer, DPB) 230 is used to store the filtered block 221. The decoded picture buffer 230 may further be used to store the same current picture or other previously filtered blocks, e.g., previously reconstructed and filtered blocks 221, of different pictures, e.g., previously reconstructed pictures, and may provide complete previously reconstructed, i.e., decoded pictures (and corresponding reference blocks and samples) and/or partially reconstructed current pictures (and corresponding reference blocks and samples), e.g., for inter prediction. In a certain example, if the reconstructed block 215 is reconstructed without in-loop filtering, the decoded picture buffer (decoded picture buffer, DPB) 230 is used to store the reconstructed block 215.

The prediction processing unit 260, also referred to as block prediction processing unit 260, is adapted to receive or obtain block 203 (current block 203 of current picture 201) and reconstructed slice data, e.g. reference samples of the same (current) picture from buffer 216 and/or reference picture data 231 of one or more previously decoded pictures from decoded picture buffer 230, and to process such data for prediction, i.e. to provide a prediction block 265 which may be an inter prediction block 245 or an intra prediction block 255.

The mode selection unit 262 may be used to select a prediction mode (e.g., intra or inter prediction mode) and/or a corresponding prediction block 245 or 255 used as the prediction block 265 to calculate the residual block 205 and reconstruct the reconstructed block 215.

Embodiments of mode selection unit 262 may be used to select the prediction mode (e.g., from those supported by prediction processing unit 260) that provides the best match or minimum residual (minimum residual meaning better compression in transmission or storage), or that provides the minimum signaling overhead (minimum signaling overhead meaning better compression in transmission or storage), or both. The mode selection unit 262 may be adapted to determine a prediction mode based on a rate-distortion optimization (rate distortion optimization, RDO), i.e. to select the prediction mode that provides the least rate-distortion optimization, or to select a prediction mode for which the associated rate-distortion at least meets a prediction mode selection criterion.

The prediction processing performed by an instance of encoder 20 (e.g., by prediction processing unit 260) and the mode selection performed (e.g., by mode selection unit 262) will be explained in detail below.

As described above, the encoder 20 is configured to determine or select the best or optimal prediction mode from a (predetermined) set of prediction modes. The set of prediction modes may include, for example, intra prediction modes and/or inter prediction modes.

The set of intra prediction modes may include 35 different intra prediction modes, or may include 67 different intra prediction modes, or may include the intra prediction mode defined in h.266 in progress.

The set of inter prediction modes depends on the available reference pictures (i.e. at least part of the decoded pictures stored in the DBP 230 as described before) and other inter prediction parameters, e.g. on whether the entire reference picture is used or only a part of the reference picture is used, e.g. a search window area surrounding the area of the current block, to search for the best matching reference block, and/or on whether pixel interpolation like half-pixel and/or quarter-pixel interpolation is applied, for example.

In addition to the above prediction modes, a skip mode and/or a direct mode may also be applied.

The prediction processing unit 260 may be further operative to partition the block 203 into smaller block partitions or sub-blocks, for example, by iteratively using a quad-tree (QT) partition, a binary-tree (BT) partition, or a ternary-tree (TT) partition, or any combination thereof, and to perform prediction for each of the block partitions or sub-blocks, for example, wherein the mode selection includes selecting a tree structure of the partitioned block 203 and selecting a prediction mode applied to each of the block partitions or sub-blocks.

The inter prediction unit 244 may include a motion estimation (motion estimation, ME) unit (not shown in fig. 2) and a motion compensation (motion compensation, MC) unit (not shown in fig. 2). The motion estimation unit is used to receive or obtain a picture block 203 (current picture block 203 of the current picture 201) and a decoded picture 231, or at least one or more previously reconstructed blocks, e.g. reconstructed blocks of one or more other/different previously decoded pictures 231, for motion estimation. For example, the video sequence may include a current picture and a previously decoded picture 31, or in other words, the current picture and the previously decoded picture 31 may be part of, or form, a sequence of pictures that form the video sequence.

For example, encoder 20 may be configured to select a reference block from a plurality of reference blocks of the same or different pictures of a plurality of other pictures, and provide the reference picture and/or an offset (spatial offset) between a position (X, Y coordinates) of the reference block and a position of a current block to a motion estimation unit (not shown in fig. 2) as an inter prediction parameter. This offset is also called Motion Vector (MV).

The motion compensation unit is used to obtain, for example, receive inter prediction parameters and perform inter prediction based on or using the inter prediction parameters to obtain the inter prediction block 245. The motion compensation performed by the motion compensation unit (not shown in fig. 2) may involve fetching or generating a prediction block based on motion/block vectors determined by motion estimation (possibly performing interpolation of sub-pixel accuracy). Interpolation filtering may generate additional pixel samples from known pixel samples, potentially increasing the number of candidate prediction blocks available for encoding a picture block. Upon receiving the motion vector for the PU of the current picture block, motion compensation unit 246 may locate the prediction block to which the motion vector points in a reference picture list. Motion compensation unit 246 may also generate syntax elements associated with the blocks and video slices for use by video decoder 30 in decoding the picture blocks of the video slices.

The intra prediction unit 254 is used to obtain, for example, a picture block 203 (current picture block) that receives the same picture and one or more previously reconstructed blocks, for example, reconstructed neighboring blocks, for intra estimation. For example, encoder 20 may be configured to select an intra-prediction mode from a plurality of intra-prediction modes.

Embodiments of encoder 20 may be used to select an intra-prediction mode based on optimization criteria, such as based on a minimum residual (e.g., the intra-prediction mode that provides a prediction block 255 most similar to current picture block 203) or minimum rate distortion.

The intra prediction unit 254 is further adapted to determine an intra prediction block 255 based on intra prediction parameters like the selected intra prediction mode. In any case, after the intra-prediction mode for the block is selected, the intra-prediction unit 254 is also configured to provide the intra-prediction parameters, i.e., information indicating the selected intra-prediction mode for the block, to the entropy encoding unit 270. In one example, intra-prediction unit 254 may be used to perform any combination of the intra-prediction techniques described below.

The entropy encoding unit 270 is configured to apply an entropy encoding algorithm or scheme (e.g., a variable length coding (variable length coding, VLC) scheme, a Context Adaptive VLC (CAVLC) scheme, an arithmetic coding scheme, a context adaptive binary arithmetic coding (context adaptive binary arithmetic coding, CABAC), a syntax-based context-based binary arithmetic coding (SBAC), a probability interval partitioning entropy (probability interval partitioning entropy, PIPE) coding, or other entropy encoding methods or techniques) to one or all of the quantized residual coefficients 209, inter-prediction parameters, intra-prediction parameters, and/or loop filter parameters (or not) to obtain encoded picture data 21 that may be output by the output 272 in the form of, for example, an encoded bitstream 21. The encoded bitstream may be transmitted to video decoder 30 or archived for later transmission or retrieval by video decoder 30. Entropy encoding unit 270 may also be used to entropy encode other syntax elements of the current video slice being encoded.

Other structural variations of video encoder 20 may be used to encode the video stream. For example, the non-transform based encoder 20 may directly quantize the residual signal without a transform processing unit 206 for certain blocks or frames. In another embodiment, encoder 20 may have quantization unit 208 and inverse quantization unit 210 combined into a single unit.

Fig. 3 illustrates an exemplary video decoder 30 for implementing the techniques of this application. Video decoder 30 is operative to receive encoded picture data (e.g., encoded bitstream) 21, e.g., encoded by encoder 20, to obtain decoded picture 231. During the decoding process, video decoder 30 receives video data, such as an encoded video bitstream representing picture blocks of an encoded video slice and associated syntax elements, from video encoder 20.

In the example of fig. 3, decoder 30 includes entropy decoding unit 304, inverse quantization unit 310, inverse transform processing unit 312, reconstruction unit 314 (e.g., summer 314), buffer 316, loop filter 320, decoded picture buffer 330, and prediction processing unit 360. The prediction processing unit 360 may include an inter prediction unit 344, an intra prediction unit 354, and a mode selection unit 362. In some examples, video decoder 30 may perform a decoding pass that is substantially reciprocal to the encoding pass described with reference to video encoder 20 of fig. 2.

Entropy decoding unit 304 is used to perform entropy decoding on encoded picture data 21 to obtain, for example, quantized coefficients 309 and/or decoded encoding parameters (not shown in fig. 3), e.g., any or all of inter-prediction, intra-prediction parameters, loop filter parameters, and/or other syntax elements (decoded). Entropy decoding unit 304 is further configured to forward inter-prediction parameters, intra-prediction parameters, and/or other syntax elements to prediction processing unit 360. Video decoder 30 may receive syntax elements at the video stripe level and/or the video block level.

Inverse quantization unit 310 may be functionally identical to inverse quantization unit 110, inverse transform processing unit 312 may be functionally identical to inverse transform processing unit 212, reconstruction unit 314 may be functionally identical to reconstruction unit 214, buffer 316 may be functionally identical to buffer 216, loop filter 320 may be functionally identical to loop filter 220, and decoded picture buffer 330 may be functionally identical to decoded picture buffer 230.

The prediction processing unit 360 may include an inter prediction unit 344 and an intra prediction unit 354, where the inter prediction unit 344 may be similar in function to the inter prediction unit 244 and the intra prediction unit 354 may be similar in function to the intra prediction unit 254. The prediction processing unit 360 is typically used to perform block prediction and/or to obtain a prediction block 365 from the encoded data 21, as well as to receive or obtain prediction related parameters and/or information about the selected prediction mode (explicitly or implicitly) from, for example, the entropy decoding unit 304.

When a video slice is encoded as an intra-coded (I) slice, the intra-prediction unit 354 of the prediction processing unit 360 is used to generate a prediction block 365 for a picture block of the current video slice based on the signaled intra-prediction mode and data from a previously decoded block of the current frame or picture. When a video frame is encoded as an inter-coded (i.e., B or P) slice, an inter-prediction unit 344 (e.g., a motion compensation unit) of prediction processing unit 360 is used to generate a prediction block 365 for a video block of the current video slice based on the motion vector and other syntax elements received from entropy decoding unit 304. For inter prediction, a prediction block may be generated from one reference picture within one reference picture list. Video decoder 30 may construct a reference frame list based on the reference pictures stored in DPB 330 using default construction techniques: list 0 and list 1.

The prediction processing unit 360 is configured to determine prediction information for a video block of a current video slice by parsing the motion vector and other syntax elements, and generate a prediction block for the current video block being decoded using the prediction information. For example, prediction processing unit 360 uses some syntax elements received to determine a prediction mode (e.g., intra or inter prediction) for encoding video blocks of a video slice, an inter prediction slice type (e.g., B slice, P slice, or GPB slice), construction information for one or more of the reference picture lists of the slice, motion vectors for each inter-encoded video block of the slice, inter prediction state for each inter-encoded video block of the slice, and other information to decode video blocks of the current video slice.

Inverse quantization unit 310 may be used to inverse quantize (i.e., inverse quantize) the quantized transform coefficients provided in the bitstream and decoded by entropy decoding unit 304. The inverse quantization process may include using quantization parameters calculated by video encoder 20 for each video block in a video stripe to determine the degree of quantization that should be applied and likewise the degree of inverse quantization that should be applied.

The inverse transform processing unit 312 is configured to apply an inverse transform (e.g., an inverse DCT, an inverse integer transform, or a conceptually similar inverse transform process) to the transform coefficients in order to generate a residual block in the pixel domain.

A reconstruction unit 314 (e.g., a summer 314) is used to add the inverse transform block 313 (i.e., the reconstructed residual block 313) to the prediction block 365 to obtain a reconstructed block 315 in the sample domain, e.g., by adding sample values of the reconstructed residual block 313 to sample values of the prediction block 365.

Loop filter unit 320 is used (during or after the encoding cycle) to filter reconstructed block 315 to obtain filtered block 321, to smooth pixel transitions or improve video quality. In one example, loop filter unit 320 may be used to perform any combination of the filtering techniques described below. Loop filter unit 320 is intended to represent one or more loop filters, such as a deblocking filter, a sample-adaptive offset (SAO) filter, or other filters, such as a bilateral filter, an adaptive loop filter (adaptive loop filter, ALF), or a sharpening or smoothing filter, or a collaborative filter. Although loop filter unit 320 is shown in fig. 3 as an in-loop filter, in other configurations loop filter unit 320 may be implemented as a post-loop filter.

The decoded video blocks 321 in a given frame or picture are then stored in a decoded picture buffer 330 that stores reference pictures for subsequent motion compensation.

Decoder 30 is for outputting decoded picture 31, e.g., via output 332, for presentation to a user or for viewing by a user.

Other variations of video decoder 30 may be used to decode the compressed bitstream. For example, decoder 30 may generate the output video stream without loop filter unit 320. For example, the non-transform based decoder 30 may directly inverse quantize the residual signal without an inverse transform processing unit 312 for certain blocks or frames. In another embodiment, the video decoder 30 may have an inverse quantization unit 310 and an inverse transform processing unit 312 combined into a single unit.

Fig. 4 is a schematic diagram of the structure of a video decoding apparatus 400 (e.g., a video encoding apparatus 400 or a video decoding apparatus 400) according to an embodiment of the present invention. The video coding apparatus 400 is adapted to implement the embodiments described herein. In one embodiment, video coding device 400 may be a video decoder (e.g., video decoder 30 of fig. 1A) or a video encoder (e.g., video encoder 20 of fig. 1A). In another embodiment, video coding device 400 may be one or more components of video decoder 30 of fig. 1A or video encoder 20 of fig. 1A described above.

The video coding apparatus 400 includes: an ingress port 410 and a receiving unit (Rx) 420 for receiving data, a processor, logic unit or Central Processing Unit (CPU) 430 for processing data, a transmitter unit (Tx) 440 and an egress port 450 for transmitting data, and a memory 460 for storing data. The video decoding apparatus 400 may further include a photoelectric conversion component and an electro-optical (EO) component coupled to the inlet port 410, the receiver unit 420, the transmitter unit 440, and the outlet port 450 for the outlet or inlet of optical or electrical signals.

The processor 430 is implemented in hardware and software. Processor 430 may be implemented as one or more CPU chips, cores (e.g., multi-core processors), FPGAs, ASICs, and DSPs. Processor 430 is in communication with inlet port 410, receiver unit 420, transmitter unit 440, outlet port 450, and memory 460. The processor 430 includes a coding module 470 (e.g., an encoding module 470 or a decoding module 470). The encoding/decoding module 470 implements the embodiments disclosed above. For example, the encoding/decoding module 470 implements, processes, or provides various encoding operations. Thus, substantial improvements are provided to the functionality of the video coding device 400 by the encoding/decoding module 470 and affect the transition of the video coding device 400 to different states. Alternatively, the encoding/decoding module 470 is implemented in instructions stored in the memory 460 and executed by the processor 430.

Memory 460 includes one or more disks, tape drives, and solid state drives, and may be used as an overflow data storage device for storing programs when selectively executing such programs, as well as storing instructions and data read during program execution. Memory 460 may be volatile and/or nonvolatile and may be Read Only Memory (ROM), random Access Memory (RAM), random access memory (TCAM) and/or Static Random Access Memory (SRAM).

Fig. 5 is a simplified block diagram of an apparatus 500 that may be used as either or both of the source device 12 and the destination device 14 in fig. 1A, according to an example embodiment. Apparatus 500 may implement the techniques of this application and apparatus 500 for implementing chroma block prediction may take the form of a computing system comprising multiple computing devices or a single computing device such as a mobile phone, tablet, laptop, notebook, desktop, or the like.

The processor 502 in the apparatus 500 may be a central processor. Processor 502 may be any other type of device or devices capable of manipulating or processing information, either as is known or later developed. As shown, while the disclosed embodiments may be practiced with a single processor, such as processor 502, advantages in speed and efficiency may be realized with more than one processor.

In an embodiment, the Memory 504 in the apparatus 500 may be a Read Only Memory (ROM) device or a random access Memory (random access Memory, RAM) device. Any other suitable type of storage device may be used as memory 504. Memory 504 may include code and data 506 that is accessed by processor 502 using bus 512. Memory 504 may further include an operating system 508 and an application 510, application 510 containing at least one program that permits processor 502 to perform the methods described herein. For example, application 510 may include applications 1 through N, applications 1 through N further including video encoding applications that perform the methods described herein. The apparatus 500 may also contain additional memory in the form of a secondary memory 514, which secondary memory 514 may be, for example, a memory card for use with a mobile computing device. Because video communication sessions may contain a large amount of information, such information may be stored in whole or in part in slave memory 514 and loaded into memory 504 for processing as needed.

The apparatus 500 may also include one or more output devices, such as a display 518. In one example, display 518 may be a touch-sensitive display that combines the display and touch-sensitive elements operable to sense touch inputs. A display 518 may be coupled to the processor 502 by a bus 512. Other output devices may be provided in addition to the display 518 that permit a user to program or otherwise use the apparatus 500, or other output devices may be provided as alternatives to the display 518. When the output device is a display or comprises a display, the display may be implemented in different ways, including by a liquid crystal display (liquid crystal display, LCD), cathode-ray tube (CRT) display, plasma display or light emitting diode (light emitting diode, LED) display, such as an Organic LED (OLED) display.

The apparatus 500 may also include or be in communication with an image sensing device 520, the image sensing device 520 being, for example, a camera or any other image sensing device 520 now available or hereafter developed that can sense images, such as images of a user operating the apparatus 500. The image sensing device 520 may be placed directly facing the user running the apparatus 500. In an example, the position and optical axis of the image sensing device 520 may be configured such that its field of view includes an area proximate to the display 518 and the display 518 is visible from that area.

The apparatus 500 may also include or be in communication with a sound sensing device 522, such as a microphone or any other sound sensing device now available or later developed that may sense sound in the vicinity of the apparatus 500. The sound sensing device 522 may be placed directly facing the user operating the apparatus 500 and may be used to receive sounds, such as speech or other sounds, emitted by the user while operating the apparatus 500.

Although the processor 502 and the memory 504 of the apparatus 500 are depicted in fig. 5 as being integrated in a single unit, other configurations may also be used. The operations of processor 502 may be distributed among a plurality of directly couplable machines, each having one or more processors, or distributed in a local area or other network. The memory 504 may be distributed across multiple machines, such as network-based memory or memory in multiple machines running the apparatus 500. Although depicted here as a single bus, the bus 512 of the apparatus 500 may be formed from multiple buses. Further, slave memory 514 may be coupled directly to other components of apparatus 500 or may be accessible over a network, and may comprise a single integrated unit, such as a memory card, or multiple units, such as multiple memory cards. Thus, the apparatus 500 may be implemented in a variety of configurations.

As described earlier in this application, color video contains chrominance components (U, V) in addition to the luminance (Y) component. Therefore, in addition to encoding the luminance component, it is also necessary to encode the chrominance component. Depending on the sampling method of the luminance component and the chrominance component in color video, there are typically YUV4:4:4, YUV4:2:2, and YUV4:2:0. As shown in fig. 6, where the crosses represent luminance component sample points and the circles represent chrominance component sample points.

4:4:4 format: indicating that the chrominance components are not downsampled;

4:2:2 format: indicating that the chrominance components are downsampled 2:1 horizontally relative to the luminance components, without vertical downsampling. For every two U sampling points or V sampling points, each row contains four Y sampling points;

4:2:0 format: representing the chroma component being downsampled horizontally by 2:1 with respect to the luma component, and downsampled vertically by 2:1.

Of these, YUV4:2:0 is the most common. In the case of video images in YUV4:2:0 sampling format, if the luminance component of an image block is an image block of size 2Mx2N, the chrominance component of the image block is an image block of size MxN. Thus, the chrominance components of an image block are also referred to herein as chrominance blocks or chrominance component blocks. The application is presented in terms of YUV4:2:0, but may also be applied to other methods of sampling luminance and chrominance components.

In the present application, a pixel point in a chrominance image (picture) is simply referred to as a chrominance sample point (chroma sample), or a chrominance point; the pixel points in the luminance image (picture) are simply referred to as luminance sample points (luma samples), or luminance points.

Similar to the luminance component, the intra-chroma prediction also uses boundary pixels of adjacent reconstructed blocks around the current chroma block as reference pixels of the current block, and maps the reference pixels to pixel points in the current chroma block according to a certain prediction mode to serve as prediction values of the pixels in the current chroma block. In contrast, since the texture of the chrominance components is generally simpler, the number of intra prediction modes for the chrominance components is generally less than for the luminance component.

The cross-component prediction mode (Cross component prediction, CCP) is also known as a cross-component intra prediction mode (Cross component intra prediction, CCIP), or Cross Component Linear Mode (CCLM) prediction mode. The CCLM prediction mode may be simply referred to as a Linear Model (LM) mode. LM mode (simply referred to as linear model, or linear mode) is a chroma intra prediction method using texture correlation between luminance and chrominance. The LM derives the current chroma block prediction value in a linear model using the reconstructed luma component, which can be expressed as:

pred _C (i，j)＝α*rec _L '(i，j)+β (1)

Wherein alpha and beta are linear model coefficients, pred _C (i, j) is the predicted value of the chroma pixel at the (i, j) position, rec _L ' i, j is a luminance reconstructed pixel value at a (i, j) position after downsampling a luminance reconstructed block (hereinafter, simply referred to as a corresponding luminance block) corresponding to the current chrominance block to the resolution of the chrominance component. For video in YUV4:2:0 format, the resolution of the luminance component is 4 times (twice each width and height) that of the chrominance component, in order to obtain a luminance block with the same resolution as the chrominance block, the luminance component needs to be downsampled to the chrominance resolution according to the same downsampling method of the chrominance component and then used.

The linear model coefficients do not need to be transmitted in coding, but instead the alpha, beta are derived using the edge pixels of the neighboring reconstructed block of the current chroma block and the luma component pixels of the corresponding position of said edge pixels. Fig. 7 illustrates one embodiment of a cross-component prediction mode (Cross component prediction, CCP). In FIG. 7, rec _L For reconstructed luma blocks (current chroma block corresponds to luma block and neighboring reference pixels), rec _L ' after downsamplingLuminance block rec _C ' is the neighboring reconstructed reference pixel of the current chroma block. The current chroma block size is WxH, the adjacent reconstructed pixels on the adjacent upper side and the adjacent reconstructed pixels on the left side are taken as reference pixels, the corresponding luma block size is 2Wx2H, and the luma block reference pixels are downsampled to the chroma resolution, so that the pixel block shown in fig. 7 (b) is obtained. Adjacent reference pixels in fig. 7 (b) and 7 (c) constitute a one-to-one correspondence.

For ease of illustration, the adjacent upper and left sides used to calculate the linear model coefficients are referred to herein as templates (templates). The adjacent upper edge is called the upper template, and the adjacent left edge is called the left template. The chroma sampling points in the upper template are called upper template chroma points, the brightness sampling points in the upper template are called upper template brightness points, and the left template chroma points and the left template brightness points can be known similarly. The template luminance points and the template chrominance points are in one-to-one correspondence, and the values of the sampling points constitute value pairs.

In the present embodiment, the template represents a set of luminance points or chrominance points used to calculate the coefficients of the linear model, where the luminance points generally need to be obtained by downsampling (since the resolution of the luminance component is different from the chrominance), denoted as Luma' samples. Chroma samples (Chroma samples) are typically the next upper row or two rows of pixels and one or two columns of pixels to the left of the current Chroma block. Fig. 8 (a) is a schematic diagram of a template in a row and a column, and fig. 8 (b) is a schematic diagram of a template in two rows and two columns.

The LM mode can effectively utilize the correlation between the luminance component and the chrominance component, and is more flexible than the direction prediction mode, thereby providing a more accurate prediction signal for the chrominance component.

In addition, there is a multi-linear model (Multiple model linear model, MMLM) mode, with a plurality of α and β. Taking two linear models as an example, there are two sets of linear model coefficients, α ₁ ，β ₁ Alpha and alpha ₂ ，β ₂ . MMLM derives the current chroma block prediction value in a linear model using the reconstructed luma component, which can be expressed as:

FIG. 9 (a) shows a schematic of MMLM mode usage templates. Similar to fig. 8 (a) and 8 (b), luminance points typically need to be obtained by downsampling (since the resolution of the luminance component is different from the chrominance), denoted as Luma' samples. Chroma samples (Chroma samples) are typically the next upper row or two rows of pixels and one or two columns of pixels to the left of the current Chroma block. In fig. 9 (a), two rows and two columns are used as the template.

Fig. 9 (b) shows a schematic of the use of templates for the multidirectional linear model predictive mode (multi-direction linear model, MDLM). Similar to fig. 8 (a) and 8 (b), luminance points typically need to be obtained by downsampling (since the resolution of the luminance component is different from the chrominance), denoted as Luma' samples. Unlike the LM mode in which the upper template and the left template (L-type template) are simultaneously used, the multidirectional linear model prediction mode (MDLM) may use only the upper template or the left template for calculating the linear model coefficients.

In addition, as shown in fig. 9 (b), in order to provide a larger template (more reference pixels are used to calculate the linear model coefficients) to obtain more stable linear model coefficients, the size of the upper template or the left template is generally lengthened and enlarged in the MDLM mode.

The mode of performing linear model coefficient calculation using only the upper template may be referred to as an LMA (may also be referred to as an LMT) mode, and the mode of performing linear model coefficient calculation using only the left template may be referred to as an LML mode.

In a specific encoding process, the current chroma block uses RDO criteria to select the best mode from the LM mode and other chroma modes. The LM mode includes, but is not limited to, an LMA mode and an LML mode.

The embodiment of the application provides a linear model coefficient deriving method for reducing LM complexity. Specifically, the template luminance points and the corresponding chromaticity points are divided into two types (sets) according to the average value of the template luminance points, and the luminance average value and the chromaticity average value in the two types are calculated respectively. And obtaining a linear model coefficient based on the two luminance average values and the two chrominance average values.

It should be noted that, in the embodiments of the present application, the positions, the number, and the acquisition methods of the template luminance points and the template chrominance points are not limited. For example, a row and a column of pixel points may be used; two rows and two columns of pixel points can also be used; or only one or two rows of pixels are used; or only one or two columns of pixels are used. The template brightness point can be obtained by a downsampling method or a non-downsampling method. And then obtaining template brightness points and template chromaticity points which are in one-to-one correspondence.

In addition, in the embodiment of the present application, the construction/derivation process of the chroma prediction block/the chroma block prediction value is mainly used in the intra prediction process under the condition that the current chroma block is known to adopt the LM prediction mode, and the process exists at both the encoding end and the decoding end. Specifically, for the decoding end, the decoding end may parse the code stream to obtain indication information, where the indication information is used to indicate that the intra-frame prediction mode adopted in current decoding is a linear model LM mode.

For convenience of description, the value pair set formed by the value of the template luminance point and the value of the template chrominance point is recorded as Ω, the set formed by the value of the template luminance point is recorded as ψ, and the set formed by the value of the template chrominance point is recorded as Φ.

Ω＝{(L ₀ ，C ₀ )，(L ₁ ，C ₂ )...(L _n ，C _n )...(L _N-1 ，C _N-1 )}

Ψ＝{L ₀ ，L ₁ ，...L _n ，...L _N-1 }

Φ＝{C ₀ ，C ₁ ，...C _n ，...C _N-1 }

Where N is the number of template pixels used to determine the coefficients of the linear model.

The following description describes a method of predicting a chroma block in connection with the following embodiments one to two. In particular, the following embodiments one through two may be performed by the system or apparatus of the embodiments of FIGS. 1A-5.

Example 1

As shown at 1000 in fig. 10, a mean value of the template luminance points is first obtained, and then the template luminance points are divided into two sets according to whether the template luminance points are greater than the mean value. Since the template luminance points and the template chrominance points are in one-to-one correspondence, the corresponding template chrominance points are also divided into two sets. And then respectively calculating the luminance average value and the chrominance average value in each set, and deriving linear model coefficients based on the two luminance average values and the chrominance average values for predicting the chrominance blocks. An embodiment one may be implemented by the apparatus for decoding a video stream, or the apparatus for encoding a video stream, or the decoding apparatus, or the encoding apparatus of the embodiments of fig. 1A-5. The following is a detailed description.

Step 1002, a mean of luminance points in a luminance block template is obtained. The luminance block corresponds to a chrominance block that needs to be predicted.

The range of the template is a template area of a luminance block corresponding to the current chroma block, and the template area includes an upper template and/or a left template, which can be specifically described with reference to fig. 7-9. One row of the upper template may be searched, one row of the upper template and one column of the left template may be searched, two rows of the upper template may be searched, or two rows of the upper template and two columns of the left template may be searched.

For example, if the average value of the template brightness points is L _mean ，Ψ＝{L ₀ ，L ₁ ，...L _n ，...L _N-1 }，

Then

Wherein N is the number of brightness points in the template, L _n The value of the nth brightness point is equal to or more than 0 and equal to or less than N-1.

Step 1004, dividing the luminance points in the luminance block template into two luminance sets, wherein the value of the luminance points in the first luminance set is smaller than the average value of the luminance points in the luminance block template, and the value of the luminance points in the second luminance set is larger than the average value of the luminance points in the luminance block template.

Specifically, the template luminance point can be pressed to determine whether it is larger than L _mean Is divided into two sets, ψ _L The point number in is S, ψ _R The number of points in (a) is T. S+t=n is satisfied. Psi＝Ψ _L +Ψ _R 。

Ψ _L ＝{L _i0 ,L _i1 ,L _i2 ,L _is ,...L _iS },Ψ _L The luminance value L in _is ≤L _mean ；

Ψ _R ＝{L _j0 ,L _j1 ,L _j2 ,L _jt ,...L _jT },Ψ _R The luminance value L in _jt ＞L _mean ；

Here is, jt.epsilon.0, N-1.

In the other of the embodiments of the present invention,

Ψ _L ＝{L _i0 ,L _i1 ,L _i2 ,L _is ,...L _iS },Ψ _L the luminance value L in _is ＜L _mean ；

Ψ _R ＝{L _j0 ,L _j1 ,L _j2 ,L _jt ,...L _jT },Ψ _R The luminance value L in _jt ≥L _mean ；

Here is, jt.epsilon.0, N-1.

That is, if the luminance points in the luminance block template include the luminance points corresponding to the average value, the luminance points corresponding to the average value are located in the first luminance set ψ _L Or at the second luminance set ψ _R . If there are multiple luminance points corresponding to the average value, part of the luminance points may be located in the first luminance set, and part of the luminance points may be located in the second luminance set.

Since the template luminance points and the template chrominance points are in one-to-one correspondence, the template chrominance points are correspondingly divided into two sets Φ=Φ _L +Φ _R ：

Φ _L ＝{C _i0 ,C _i1 ,C _i2 ,C _is ,...C _iS },

Φ _R ＝{C _j0 ,C _j1 ,C _j2 ,C _jt ,...C _jT }。

Step 1006, obtaining a first luminance average value according to the values of the luminance points in the first luminance set, and obtaining a first chrominance average value according to the values of the chrominance points corresponding to the luminance points in the first luminance set.

Specifically, if the first luminance average value is L _Lmean The first chrominance mean value is C _Lmean Then

Wherein L is _is Is the value of the is-th brightness point, C _is Is equal to or more than 0 and equal to or less than S-1, is epsilon [0, N-1] as the value of the is-th chromaticity point]L _is ≤L _mean Or L _is ＜L _mean . Taking fig. 11 as an example, an a pixel point is determined, and the chromaticity value of the a pixel point is C _Lmean A brightness value of L _Lmean 。

Step 1008, obtaining a second luminance average value according to the values of the luminance points in the second luminance set, and obtaining a second chrominance average value according to the values of the chrominance points corresponding to the luminance points in the second luminance set.

Specifically, if the second luminance average value is L _Rmean The second chromaticity average value is C _Rmean Then

Wherein L is _jt C is the value of jt brightness point _jt For the value of the jt chromaticity point, jt is more than or equal to 0 and less than or equal to T-1, jt E [0, N-1 ]]L _jt ＞L _mean Or L _jt ≥L _mean . Taking fig. 11 as an example, a B pixel point is determined, and the chromaticity value of the B pixel point is C _Rmean A brightness value of L _Rmean 。

Steps

1006 and 1008 are not sequential.

Step 1010, obtaining a first set of linear model coefficients according to the first luminance average and the first chrominance average, and the second luminance average and the second chrominance average.

Specifically, based on L _Lmean ，L _Rmean ,C _Lmean ,C _Rmean Linear model coefficients alpha and beta are obtained.

In another embodiment, β may also be calculated from the average of luminance template pixel values and the average of chrominance template pixel values:

β＝C _mean -α*L _mean

here the number of the elements is the number,

wherein N is the number of chroma points in the chroma block template, C _n N is equal to or greater than 0 and equal to or less than N-1, which is the value of the nth chromaticity point.

Step 1012, obtaining a predicted value of a chroma point of the chroma block according to the value of the luma point of the luma block and the first set of linear model coefficients.

Specifically, after the linear model coefficients are obtained, the predicted values of the chromaticity points of the chromaticity block may be obtained with reference to formula (1).

According to the method in the first embodiment of the invention, the template luminance points are divided into two sets according to the average value, the corresponding template chrominance points are also divided into two sets, the luminance average value and the chrominance average value in each set are calculated respectively, and the linear model coefficient is derived based on the two luminance average values and the chrominance average value. Compared with the prior art that the linear model coefficient is obtained based on the least square method, the method and the device can reduce the complexity of the linear model; compared with the prior art that linear model coefficients are obtained based on an extremum method, the embodiment of the invention can improve robustness, so that the embodiment of the invention can improve the efficiency of chroma encoding and decoding.

Example two

In contrast to the first embodiment, the two linear models are obtained by using the classification and class mean methods. Firstly, according to the average value of the template brightness points, the brightness points are divided into two classes, and the corresponding chromaticity points are also divided into two classes. Each class derives linear model coefficients using the method of embodiment one, resulting in two linear models. And then obtaining the predicted value of the chroma block by adopting a formula (2) based on the two obtained linear models.

The prediction method of the chroma block will be described with reference to the embodiment of fig. 12.

Step 1202 is similar to step 1002 of the first embodiment, and step 1204 is similar to step 1004 of the first embodiment, and will not be described again.

Step 1206: and obtaining a first brightness average value according to the brightness point value in the first brightness set.

Specifically, if the first luminance average value is L _Lmean Then

Wherein L is _is Is equal to or more than 0 and equal to or less than S-1, is epsilon [0, N-1 ] as the value of the is-th brightness point]L _is ≤L _mean Or L _is ＜L _mean 。

Step 1208, obtaining a second luminance average according to the luminance points in the second luminance set.

Specifically, if the second luminance average value is L _Rmean Then

Wherein L is _jt For the value of the jt brightness point, jt is more than or equal to 0 and less than or equal to T-1, jt E [0, N-1 ]]L _jt ＞L _mean Or L _jt ≥L _mean 。

Steps

1206 and 1208 are not sequential.

The method of embodiment one is then performed on the first luminance set and the second luminance set, respectively. The details are as follows.

In step 1302, the luminance points in the first luminance set are divided into two luminance sets, the value of the luminance point in the third luminance set is smaller than the first luminance average value, and the value of the luminance point in the fourth luminance set is larger than the first luminance average value.

Specifically, the first luminance set may be determined as whether or not the first luminance average value L is greater than _Lmean Divided into two sets ψ _LL And psi is _LR 。

Ψ _LL ＝{L _e0 ,L _e1 ,L _e2 ,L _ew ,...L _eW },Ψ _LL The luminance value L in _ew ≤L _Lmean ；

Ψ _LR ＝{L _f0 ,L _f1 ,L _f2 ,L _fv ,...L _fV },Ψ _LR The luminance value L in _fv ＞L _Lmean ；

Here, w+v=s.

In the other of the embodiments of the present invention,

Ψ _LL ＝{L _e0 ,L _e1 ,L _e2 ,L _ew ,...L _eW },Ψ _LL the luminance value L in _ew ＜L _Lmean ；

Ψ _LR ＝{L _f0 ,L _f1 ,L _f2 ,L _fv ,...L _fV },Φ _LR The luminance value L in _fv ≥L _Lmean ；

Because the template luminance points and the template chrominance points are in one-to-one correspondence, the template chrominance points are correspondingly divided into two sets to correspondingly obtain chrominance point subsets:

Φ _LL ＝{C _e0 ,C _e1 ,C _e2 ,C _ew ,...C _eW }

Φ _LR ＝{C _f0 ,C _f1 ,C _f2 ,C _fv ,...C _fV }。

reference may be made specifically to the description of 1004.

Step 1304, obtaining a third luminance average value according to the luminance point values in the third luminance set; and obtaining a third chroma mean value according to the value of the chroma point corresponding to the brightness point in the third brightness set.

Specifically, if the third luminance average value is L _LLmean The third average value of the three colors is C _LLmean Then

Taking fig. 13 as an example, an A1 pixel point is determined, and the chromaticity value of the A1 pixel point is C _LLmean A brightness value of L _LLmean 。

Step 1306, obtaining a fourth luminance average value according to the luminance point values in the fourth luminance set; and obtaining a fourth chromaticity mean value according to the value of the chromaticity point corresponding to the brightness point in the fourth brightness set.

Similarly, a fourth luminance average value L is obtained _LRmean And the fourth chromaticity average value is C _LRmean 。

Taking fig. 13 as an example, a B1 pixel point is determined, and the chromaticity value of the B1 pixel point is C _LRmean A brightness value of L _LRmean 。

With specific reference to 1008.

Step 1308, obtaining a first set of linear model coefficients according to the third luminance average and the third chrominance average, and the fourth luminance average and the fourth chrominance average.

Specifically, the third luminance average value is L _LLmean The third average value of the three colors is C _LLmean The fourth brightness average value is L _LRmean The fourth chromaticity average value is C _LRmean The first set of linear model coefficients alpha ₁ And beta ₁ Is that

In another embodiment, β ₁ Or according to the average value L of the pixel values in the first brightness set _Lmean Mean value C of pixel values in first chrominance set _Lmean And (3) calculating:

β ₁ ＝C _Lmean -α ₁ *L _Lmean

wherein the method comprises the steps of

，C _is Is equal to or more than 0 and equal to or less than S-1, is epsilon [0, N-1 ] as the value of the is-th chromaticity point]。

Steps 1402-1408 are similar to steps 1302-1308 and there is no sequential division.

Step 1402, dividing the luminance points in the second luminance set into two luminance sets, wherein the value of the luminance point in the fifth luminance set is smaller than the second luminance average value, and the value of the luminance point in the sixth luminance set is larger than the second luminance average value.

Specifically, the second luminance set may be determined as to whether or not the second luminance average value L is greater than _Rmean Divided into two sets ψ _RL And psi is _RR 。

Ψ _RL ＝{L _g0 ,L _g1 ,L _g2 ,L _gm ,...L _gM },Ψ _RL The luminance value L in _gm ≤L _Rmean ；

Ψ _RR ＝{L _h0 ,L _h1 ,L _h2 ,L _hk ,...L _hK },Ψ _RR The luminance value L in _hk ＞L _Rmean ；

Here, m+k=t.

In the other of the embodiments of the present invention,

Ψ _RL ＝{L _g0 ,L _g1 ,L _g2 ,L _gm ,...L _gM },Ψ _RL the luminance value L in _gm ＜L _Rmean ；

Ψ _RR ＝{L _h0 ,L _h1 ,L _h2 ,L _hk ,...L _hK },Ψ _RR The luminance value L in _hk ≥L _Rmean ；

Φ _RL ＝{C _g0 ,C _g1 ,C _g2 ,C _gm ,...C _gM }

Φ _RR ＝{C _h0 ,C _h1 ,C _h2 ,C _hk ,...C _hK }。

reference may be made specifically to the description of 1004.

Step 1404, obtaining a fifth luminance average value according to the luminance points in the fifth luminance set; and obtaining a fifth chromaticity mean value according to the value of the chromaticity point corresponding to the brightness point in the fifth brightness set.

Similarly, a fifth luminance average value L can be obtained _RLmean Fifth chromaticity mean C _RLmean 。

Taking fig. 13 as an example, an A2 pixel point is determined, and the chromaticity value of the A2 pixel point is C _RLmean A brightness value of L _RLmean 。

Step 1406, obtaining a sixth luminance average value according to the luminance point values in the sixth luminance set; and obtaining a sixth chromaticity mean value according to the value of the chromaticity point corresponding to the brightness point in the sixth brightness set.

Similarly, a sixth luminance average value L can be obtained _RRmean The sixth chromaticity average value is C _RRmean 。

Taking fig. 13 as an example, a B2 pixel point is determined, and the chromaticity value of the B2 pixel point is C _RRmean A brightness value of L _RRmean 。

With specific reference to 1008.

In step 1408, a second set of linear model coefficients is obtained according to the fifth luminance average and the fifth chrominance average, and the sixth luminance average and the sixth chrominance average.

Specifically, the fifthThe average brightness value is L _RLmean The fifth chromaticity average value is C _RLmean The sixth brightness average value is L _RRmean The sixth chromaticity average value is C _RRmean The second three sets of linear model coefficients alpha ₂ ，β ₂ Is that

In another embodiment, β ₂ Or according to the average value L of the pixel values in the second brightness set _Rmean And the mean value C of the pixel values in the second chromaticity set _Rmean And (3) calculating:

β ₂ ＝C _Rmean -α ₂ *L _Rmean

wherein the method comprises the steps of

，C _jt The value of the jt chromaticity point is equal to or more than 0 and equal to or less than T-1.

Step 1212: and obtaining a predicted value of a chromaticity point of the chromaticity block according to the value of the brightness point of the brightness block, the second group of linear model coefficients and the third group of linear model coefficients.

Specifically, the predicted value of the current chroma block is then obtained according to formula (2) based on the reconstructed value of the luma block.

In other embodiments, the third luminance set may be subdivided into two or more luminance sets according to a third luminance mean. Similarly, the fourth, fifth, sixth luminance set may be subdivided into two or more luminance sets.

Compared with the method for obtaining the linear model coefficients based on the least square method in the prior art, the method for obtaining the two linear models by using the mean value method can reduce the complexity of the linear models, so that the method for obtaining the linear model coefficients can improve the efficiency of chroma coding and decoding.

As shown in embodiment one, β may be calculated from the mean of luminance template pixel values and the mean of chrominance template pixel values:

β＝C _mean -α*L _mean

here it relates to C _mean L and _mean calculation of values for the MDLM, the LMA will directly calculate the two averages using the sample values in the upper template, and the LML will directly calculate the two averages using the sample values in the left template. Embodiments three to five are described in detail.

Example III

The third embodiment is to obtain the predicted value of the current chroma block. As shown in fig. 14, W is the width of the current chroma block and H is the height of the current chroma block.

For the MDLM mode, W1 is the number of upper template sampling points and H1 is the number of left template sampling points. Here, W1> =w, H1> =h.

For the LMT mode, in order to obtain the mean value for calculating β, a sampling point of the A1 portion is used, and the length of the A1 portion is W. In this embodiment, the W sampling point is obtained from the upper template sampling point to calculate the average value of the luminance points in the luminance block template. For example, the W luminance points include adjacent pixel points A1 above the luminance block.

For the LML mode, in order to obtain the mean value for calculating β, a sampling point of the L1 portion is used, and the length of the L1 portion is H. In this embodiment, the H sample point is obtained from the left template sample point to calculate the average value of the luminance points in the luminance block template. For example, the H luminance points include adjacent pixel points L1 to the left of the luminance block.

In addition, when calculating the average value, a sampling step length method may be used to reduce the number of sampling points. The sampling step size can be 2,4,8 and …

Example IV

The fourth embodiment is to obtain the predicted value of the current chroma block. W is the width of the current chroma block and H is the height of the current chroma block.

For the MDLM mode, as shown in fig. 15, W1 is the number of upper template sampling points, and H1 is the number of left template sampling points. Here, W1> =w, H1> =h.

For the LMT mode, in order to obtain the average value for calculating β, sampling points of the right portions of A2 (upper right) and A1 (upper right) are used, and the lengths of the right portions of A2 and A1 are W. In this embodiment, the W sampling point is obtained from the upper template sampling point to calculate the average value of the luminance points in the luminance block template. Wherein, the sampling points in A2 are available (available). If the width of A2 is W, calculating the average value of the brightness points in the brightness block template by using only the sampling points in A2; if the width of A2 is less than W, then the pixel to the right of A2 is not available (un-available). For example, the W luminance points include an upper right adjacent pixel point A2 of the luminance block; or W luminance points include an adjacent pixel point A1 above a luminance block and an adjacent pixel point A2 above the right of the luminance block.

For the LML mode, in order to obtain the average value for calculating β, sampling points of the lower side portions of L2 (lower left) and L1 (left) are used, and the lengths of the lower side portions of L2 and L1 are H. In this embodiment, the H sample point is obtained from the left template sample point to calculate the average value of the luminance points in the luminance block template. Wherein, the sampling points in L2 are available (available). If the length of L2 is H, calculating the average value of the brightness points in the brightness block template by using only the sampling points in L2; if L2 is less than H in length, then the pixels on the underside of L2 are not available (un-available). For example, the H luminance points include adjacent pixel points L2 at the lower left of the luminance block; or the H luminance points include a neighboring pixel point L1 on the left of the luminance block and a neighboring pixel point L2 on the lower left of the luminance block.

Example five

When the number of pixel points samples in the upper template or the left template is the power of non-2, in order to obtain the mean value for calculating beta by using the shift operation, the division operation caused by the need of calculating the mean value is avoided. Similar to embodiment three or four, W is the width of the current chroma block and H is the height of the current chroma block.

For the LMT mode, in order to obtain the mean value for calculating β, as shown in fig. 16, sampling points of the A1, A2, and A3 portions may be used. The three parts have lengths of W2, W2 being a power of 2 value, and being a minimum value not smaller than W1. The A3 part is obtained by a padding (padding) operation, for example, copying the rightmost pixel value of the A2 part. For example, 2 can be used ^k Luminance points obtain the average value of the luminance points in the luminance block template, k is a natural number, wherein 2 ^k Not less than W1, and takes the minimum value.

For the LML mode, to obtain the mean value for calculating β, sampling points of the L1, L2, and L3 portions are used. The three parts have lengths of H2, H2 being a power of 2 value, and being a minimum value not less than H1. The L3 portion is obtained by a padding operation, for example, copying the pixel value of the lowest side of the L2 portion. For example, 2 can be used ^k Luminance points obtain the average value of the luminance points in the luminance block template, k is a natural number, wherein 2 ^k Not less than H1, and takes the minimum value.

In the third to fifth embodiments of the present invention, the efficiency of chroma coding and decoding may be further improved by limiting the number of luminance points in the luminance block template used when the average value is obtained.

It should be understood that the disclosure in connection with the described methods may be equally applicable to a corresponding apparatus or system for performing the methods, and vice versa. For example, if one or more specific method steps are described, the corresponding apparatus may comprise one or more units, such as functional units, to perform the one or more described method steps (e.g., one unit performing one or more steps, or multiple units each performing one or more of the multiple steps), even if such one or more units are not explicitly described or illustrated in the figures. On the other hand, if a specific apparatus is described based on one or more units such as a functional unit, for example, the corresponding method may include one step to perform the functionality of the one or more units (e.g., one step to perform the functionality of the one or more units, or multiple steps each to perform the functionality of one or more units, even if such one or more steps are not explicitly described or illustrated in the figures). Further, it is to be understood that features of the various exemplary embodiments and/or aspects described herein may be combined with each other, unless explicitly stated otherwise.

In one or more examples, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium, and executed by a hardware-based processing unit. A computer-readable medium may comprise a computer-readable storage medium corresponding to a tangible medium, such as a data storage medium or a communication medium, such as any medium that facilitates transfer of a computer program from one place to another, e.g., according to a communication protocol. In this manner, a computer-readable medium may generally correspond to (1) a non-transitory tangible computer-readable storage medium, or (2) a communication medium, such as a signal or carrier wave. Data storage media may be any available media that can be accessed by one or more computers or one or more processors to retrieve instructions, code and/or data structures for implementing the techniques described in this disclosure. The computer program product may include a computer-readable medium.

By way of example, and not limitation, such computer-readable storage media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, flash memory, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer. Also, any connection is properly termed a computer-readable medium. For example, if the instructions are transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (digital subscriber line, DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. It should be understood, however, that the computer-readable storage media and data storage media do not include connections, carrier waves, signals, or other transitory media, but are actually directed to non-transitory tangible storage media. Disk and disc, as used herein, includes Compact Disc (CD), laser disc, optical disc, digital versatile disc (digital versatile disc, DVD), floppy disk and blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

The instructions may be executed by one or more processors, such as one or more digital signal processors (digital signal processor, DSPs), general purpose microprocessors, application specific integrated circuits (application specific integrated circuit, ASICs), field programmable logic arrays (field programmable logic arrays, FPGAs), or other equivalent integrated or discrete logic circuitry. Thus, the term "processor" as used herein may refer to any of the foregoing structure or any other structure suitable for implementation of the techniques described herein. Additionally, in some aspects, the functionality described herein may be provided within dedicated hardware and/or software modules for encoding and decoding, or incorporated in a synthetic codec. Also, the techniques may be fully implemented in one or more circuits or logic elements.

The techniques of this disclosure may be implemented in a variety of devices or apparatuses including a wireless handset, an integrated circuit (integrated circuit, IC), or a collection of ICs (e.g., a chipset). The disclosure describes various components, modules, or units in order to emphasize functional aspects of the apparatus for performing the disclosed techniques, but does not necessarily require realization by different hardware units. In particular, as described above, the various units may be combined in a codec hardware unit in combination with suitable software and/or firmware, or provided by a collection of interoperable hardware units, including one or more processors as described above.

Claims

1. A method of predicting a chroma block, the method comprising:

obtaining the average value of brightness points in a brightness block template, wherein the brightness block corresponds to the chromaticity block;

dividing the brightness points in the brightness block template into two brightness sets, wherein the value of the brightness points in the first brightness set is smaller than the average value of the brightness points in the brightness block template, and the value of the brightness points in the second brightness set is larger than the average value of the brightness points in the brightness block template;

obtaining a first brightness average value according to the value of the brightness points in the first brightness set;

obtaining a first chrominance mean value according to the value of the chrominance point corresponding to the luminance point in the first luminance set;

obtaining a second brightness average value according to the value of the brightness point in the second brightness set;

obtaining a second chromaticity mean value according to the value of the chromaticity point corresponding to the brightness point in the second brightness set;

obtaining a first group of linear model coefficients according to the first luminance average value and the first chrominance average value, and the second luminance average value and the second chrominance average value;

and obtaining a predicted value of a chromaticity point of the chromaticity block according to the value of the brightness point of the brightness block and the first group of linear model coefficients.

2. The method of claim 1, wherein if the luminance points in the luminance block template include luminance points corresponding to the average value, the luminance points corresponding to the average value are located in the first luminance set or in the second luminance set.

3. The method according to claim 1 or 2, characterized in that the method further comprises:

obtaining a second set of linear model coefficients according to the luminance points and the corresponding chrominance points in the first luminance set,

obtaining a third group of linear model coefficients according to the brightness points and the corresponding chromaticity points in the second brightness set;

obtaining a predicted value of a chroma point of the chroma block from the value of the luma point of the luma block and the first set of linear model coefficients comprises: and obtaining a predicted value of a chromaticity point of the chromaticity block according to the value of the brightness point of the brightness block, the second group of linear model coefficients and the third group of linear model coefficients.

4. A method according to claim 3, characterized in that the method further comprises:

dividing the brightness points in the first brightness set into two brightness sets, wherein the value of the brightness points in the third brightness set is smaller than the first brightness average value, and the value of the brightness points in the fourth brightness set is larger than the first brightness average value;

Obtaining a third brightness average value according to the brightness point value in the third brightness set;

obtaining a third chroma mean value according to the value of the chroma point corresponding to the brightness point in the third brightness set;

obtaining a fourth brightness average value according to the brightness point value in the fourth brightness set;

obtaining a fourth chromaticity mean value according to the value of the chromaticity point corresponding to the brightness point in the fourth brightness set;

and obtaining the second group of linear model coefficients according to the third brightness average value and the third chromaticity average value, and the fourth brightness average value and the fourth chromaticity average value.

5. The method according to claim 3 or 4, characterized in that the method further comprises:

dividing the brightness points in the second brightness set into two brightness sets, wherein the value of the brightness points in the fifth brightness set is smaller than the second brightness average value, and the value of the brightness points in the sixth brightness set is larger than the second brightness average value;

obtaining a fifth brightness average value according to the brightness point values in the fifth brightness set;

obtaining a fifth chromaticity mean value according to the value of the chromaticity point corresponding to the brightness point in the fifth brightness set;

obtaining a sixth brightness average value according to the brightness point values in the sixth brightness set;

Obtaining a sixth chromaticity mean value according to the value of the chromaticity point corresponding to the brightness point in the sixth brightness set;

and obtaining the third group of linear model coefficients according to the fifth luminance average value and the fifth chrominance average value, and the sixth luminance average value and the sixth chrominance average value.

6. The method of any one of claims 1-5, wherein the luminance points in the luminance block template are obtained by downsampling a plurality of luminance pixel points adjacent to the luminance block.

7. The method of claim 6, wherein the sampling step size of the downsampling operation is a power of 2.

8. The method of any of claims 1-7, wherein the luminance points in the luminance block template comprise pixel points of one or more columns adjacent to the left of the luminance block.

9. The method according to claim 8, characterized in that the method comprises: and obtaining the average value of the brightness points in the brightness block template by adopting H brightness points, wherein H represents the height of the chroma block, and the total number of the brightness points in the brightness block template is greater than or equal to H.

10. The method of claim 9, wherein the H luminance points include adjacent pixels to the left of the luminance block and adjacent pixels to the bottom left of the luminance block.

11. The method according to any one of claims 8-10, wherein the prediction method is a multi-directional linear model, MDLM, mode prediction method, the MDLM mode being an LMA mode.

12. The method of any of claims 1-7, wherein the luminance points in the luminance block template comprise pixel points of a row immediately above or a plurality of rows immediately above the luminance block.

13. The method according to claim 12, characterized in that the method comprises: and obtaining the average value of the brightness points in the brightness block template by adopting W brightness points, wherein W represents the width of the chromaticity block, and the total number of the brightness points in the brightness block template is greater than or equal to W.

14. The method of claim 13, wherein the W luminance points include adjacent pixels above the luminance block and adjacent pixels above and to the right of the luminance block.

15. The method according to any one of claims 12-14, wherein the prediction method is a multi-directional linear model, MDLM, mode prediction method, the MDLM mode being an LML mode.

16. The method according to claim 8 or 12, characterized in that the method comprises: by 2 ^k Luminance points obtain the average value of the luminance points in the luminance block template, k is a natural number, wherein 2 ^k Not less than the total number of luminance points in the luminance block template.

17. The method of claim 16, wherein the 2 ^k The luminance points include luminance points in the luminance block template and luminance points obtained by a stuffing padding operation.

18. The method of any of claims 1-7, wherein the luminance points in the luminance block template comprise luminance pixels of one or more columns adjacent to the left of the luminance block, and wherein the luminance block is adjacent to one or more rows above.

19. The method of any one of claims 1-18, wherein the first luminance average value is L _Lmean The first chrominance mean value is C _Lmean The second brightness average value is L _Rmean The second chromaticity average value is C _Rmean The first set of linear model coefficients α and β are then:

20. the method of any one of claims 1-18, wherein the average value of luminance points in the luminance block template is L _mean The average value of the chroma points in the chroma block template is C _mean The first brightness average value is L _Lmean The first chrominance mean value is C _Lmean The second brightness average value is L _Rmean The second chromaticity average value is C _Rmean The first set of linear model coefficients α and β are then:

21. the method of any one of claims 1-20, wherein the average value of luminance points in the luminance block template is

Wherein N is the number of brightness points in the template, L _n For the value of the nth luminance point therein,

0≤n≤N-1。

22. the method of claim 21, wherein the average of chroma points in the chroma block template is

23. The method of any one of claims 1-22, wherein the number of luminance points in the first luminance set is S, and the first luminance average value L _Lmean The method comprises the following steps:

wherein the average value of the brightness points in the brightness block template is L _mean ，L _is Is the value of the is-th brightness point, is more than or equal to 0 and less than or equal to S-1, L _is ≤L _mean Or L _is ＜L _mean 。

24. The method of claim 23, wherein the first chrominance mean value C _Lmean The method comprises the following steps:

wherein C is _is Is the value of the is-th chromaticity point, and is more than or equal to 0 and less than or equal to S-1.

25. The method of any one of claims 1-24, wherein the number of luminance points in the second luminance set is T, and the second luminance average value L _Rmean The method comprises the following steps:

wherein the average value of the brightness points in the brightness block template is L _mean Wherein L is _jt Is the value of the jt brightness point, L _jt ＞L _mean Or L _jt ≥L _mean ，0≤jt≤T-1。

26. The method of claim 25, wherein the second chromaticity means C _Rmean The method comprises the following steps:

wherein C is _jt The value of the jt chromaticity point is equal to or more than 0 and equal to or less than T-1.

27. The method of claim 4, wherein the third luminance average value is L _LLmean The third average value of the three colors is C _LLmean The fourth brightness average value is L _LRmean The fourth chromaticity average value is C _LRmean Then the second set of linear model coefficients alpha ₁ And beta ₁ Is that

28. The method of claim 4, wherein the first luminance average value is L _Lmean The first chrominance mean value is C _Lmean The third brightness average value is L _LLmean The third average value of the three colors is C _LLmean The fourth brightness average value is L _LRmean The fourth chromaticity average value is C _LRmean Then the second set of linear model coefficients alpha ₁ And beta ₁ Is that

29. The method of claim 5, wherein the fifth luminance average value is L _RLmean The fifth chromaticity average value is C _RLmean The sixth brightness average value is L _RRmean The sixth chromaticity average value is C _RRmean Then the third set of linear model coefficients alpha ₂ And beta ₂ Is that

30. The method of claim 5, wherein the second luminance average value is L _Rmean The second chromaticity average value is C _Rmean The fifth brightness average value is L _RLmean The fifth chromaticity average value is C _RLmean The sixth brightness average value is L _RRmean The sixth chromaticity average value is C _RRmean Then the third set of linear model coefficients alpha ₂ And beta ₂ Is that

31. The method according to any one of claims 1-30, further comprising:

and analyzing the code stream to obtain indication information, wherein the indication information is used for indicating that the intra-frame prediction mode adopted by the current decoding is a linear model LM mode.

32. An apparatus for decoding a video stream, comprising a processor and a memory, the memory storing instructions that cause the processor to perform the method of any one of 1-31.

33. An apparatus for encoding a video stream, comprising a processor and a memory, the memory storing instructions that cause the processor to perform the method of any one of 1-30.

34. A decoding apparatus comprising: a non-volatile memory and a processor coupled to each other, the memory for storing program instructions that cause the processor to perform the method of any of claims 1-31.

35. An encoding apparatus, comprising: a non-volatile memory and a processor coupled to each other, the memory for storing program instructions that cause the processor to perform the method of any of claims 1-30.