CN110944180A

CN110944180A - Chroma block prediction method and device

Info

Publication number: CN110944180A
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: 2020-03-31
Anticipated expiration: 2038-10-17
Also published as: CN110944180B

Abstract

The embodiment of the invention provides a method and a device for predicting a chroma block. The method obtains the mean value of the brightness points in the brightness block template, then divides the template brightness points into two sets according to the mean value, and divides the corresponding template chroma points into two sets. And respectively calculating a brightness mean value and a chroma mean value in each set, and deriving a linear model coefficient based on the two brightness mean values and the corresponding chroma mean values. And then obtaining a predicted value of the chroma point of the chroma 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 coding and decoding, and more particularly, to a method and apparatus for chroma block prediction.

Background

With the rapid development of internet science and technology and the increasing abundance of human physical and mental culture, the application requirements for videos in the internet, particularly high-definition videos, are more and more, the data volume of the high-definition videos is very large, and the problem that the video coding and decoding must be firstly solved for the high-definition videos to be transmitted in the internet with limited bandwidth is the video coding and decoding problem. Video codecs are widely used in digital video applications such as broadcast digital television, video dissemination 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 mode may include an intra prediction mode (spatial prediction) and an inter prediction mode (temporal prediction). Wherein, the intra prediction mode set may include 35 different intra prediction modes, for example, non-directional modes such as DC (or mean) mode and planar mode; or a directivity pattern as defined in h.265; or may include 67 different intra prediction modes, e.g., non-directional modes such as DC (or mean) mode and planar 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 portion of the reference picture is used.

Conventional video is generally color video, and includes a chrominance component in addition to a luminance component. Therefore, in addition to encoding the luminance component, the chrominance component needs to be encoded. In the prior art, when intra-frame prediction is performed, the value of the chrominance component can be obtained by 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 an apparatus and method for chroma block prediction.

In a first aspect, the present invention relates to a method for predicting 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 a mean value of luminance points in a luminance block template, wherein the luminance block corresponds to the chrominance block; and dividing the brightness points in the brightness block template into two brightness sets, wherein the value of the brightness point 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 point in the second brightness set is larger than the average value of the brightness points in the brightness block template. Then, obtaining a first brightness mean value according to the values of the brightness points in the first brightness set; and obtaining a first chroma mean value according to the chroma point value corresponding to the brightness point in the first brightness set. Obtaining a second brightness mean value according to the values of the brightness points in the second brightness set; and obtaining a second chroma mean value according to the chroma point value 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 mean value and the first chrominance mean value, the second luminance mean value and the second chrominance mean value; and obtaining a predicted value of a chroma point of the chroma block according to the value of the brightness point of the brightness block and the first group of linear model coefficients.

Compared with the prior art that linear model coefficients are obtained based on the least square method, the method of the first aspect of the invention can reduce the complexity of the linear model; compared with the prior art that the linear model coefficient is obtained based on an extreme value method, the embodiment of the invention can improve the robustness, thereby improving the efficiency of chroma encoding and decoding.

In one embodiment, linear model coefficients β are

β＝C_mean-α*L_mean，

Wherein the mean value of the brightness points in the brightness block template is L_meanThe mean value of the chrominance points in the chrominance block template is C_mean。

Compared with the prior art that linear model coefficients are obtained based on the least square method, the method of the first embodiment of the invention can reduce the complexity of the linear model; compared with the prior art that the linear model coefficient is obtained based on an extreme value method, the method and the device can improve the accuracy of calculation.

In a second aspect, the 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 is directed 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 is presented having instructions stored thereon that, when executed, cause one or more processors to encode video data. The instructions cause the one or more processors to perform a method according to any of the possible embodiments of the first aspect.

In a fifth aspect, the invention relates to a computer program comprising program code for performing the method according to any of the possible embodiments of the first aspect when the program code runs 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 illustrate the technical solutions in the embodiments or the background art of the present application, the drawings required to be used in the embodiments or the background art of the present application will be described below.

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

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

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

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

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

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

fig. 6 shows an example YUV format sampling grid;

FIG. 7 illustrates one embodiment of a Cross Component Prediction (CCP) mode;

FIG. 8(a) shows a schematic of an upper and left template;

FIG. 8(b) shows another schematic view of an upper and left template;

FIG. 9(a) is a schematic diagram showing a template used in a Multiple Model Linear Model (MMLM) prediction mode;

FIG. 9(b) shows a schematic diagram of a multi-direction linear model (MDLM) prediction mode using a template;

FIG. 10 is a flow chart of a method according to a first embodiment of the present invention;

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

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

FIG. 13 is a diagram showing a linear model according to the second embodiment of the present invention;

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

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

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

In the following, identical reference signs refer to identical or at least functionally equivalent features, if no specific remarks are made with respect to the identical reference signs.

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 compressing) the original video picture to reduce the amount of data required to represent the video picture for more efficient storage and/or transmission. Video decoding is performed at the destination side, typically involving inverse processing with respect to the encoder, to reconstruct the video pictures. Embodiments are directed to video picture "encoding" to be understood as referring 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 methods for deriving coefficients of Linear Model (LM), one using least squares and one based on extreme values. A method of deriving a linear model system using the product of adjacent N reference pixels of a luminance block and corresponding chrominance pixels is called a method of least squares (abbreviated as least squares). By the maximum brightness value L_maxAnd a minimum luminance value L_minAnd determining the coefficients of the linear model by corresponding value pairs, namely an extreme value method. The complexity of the existing method for deriving the linear model coefficient based on the least square method is high, and the robustness of the method for deriving the linear model coefficient based on the extreme value method is poor. The embodiment of the invention provides an improved linear model coefficient derivation 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 (the currently processed or to be processed block) to obtain a residual block, transforms the residual block and quantizes the residual block in the transform domain to reduce the amount of data to be transmitted (compressed), while the decoder side applies the inverse processing portion relative to the encoder to the encoded or compressed block to reconstruct the current block for representation. In addition, the encoder replicates the decoder processing loop such that the encoder and decoder generate the same prediction (e.g., intra-prediction and inter-prediction) and/or reconstruction for processing, i.e., encoding, subsequent blocks.

The term "block" may be a portion of a picture or frame. The present application defines key terms as follows:

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

Predicting a block: the block that provides prediction for the current block is called a prediction block. For example, after traversing multiple reference blocks, a best reference block is found that will provide prediction for the current block, which is called a prediction block.

Image block signals: pixel values or sampling signals within the image block.

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

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

Fig. 1A is a conceptual or schematic block diagram depicting an exemplary encoding system 10, such as a video encoding system 10 that may utilize the techniques of the present application (the present disclosure). Encoder 20 (e.g., video encoder 20) and decoder 30 (e.g., video decoder 30) of video encoding system 10 represent examples of equipment that may be used to perform intra prediction according to various examples described in this application. 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 that decodes encoded data 13, for example.

Source device 12 includes an encoder 20 and, in a further alternative, may include a picture source 16, a pre-processing unit 18, such as picture pre-processing unit 18, and a communication interface or unit 22.

The picture source 16 may include or may be any type of picture capture device for capturing real-world pictures, for example, and/or any type of picture or comment generation device (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 obtaining and/or providing real-world pictures, computer animated pictures (e.g., screen content, Virtual Reality (VR) pictures), and/or any combination thereof (e.g., Augmented Reality (AR) pictures).

A picture can be seen as a two-dimensional array or matrix of sample points having intensity values. The sample points in the array may also be referred to as pixels (short for pixels) or pels (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 the RBG format or color space, a picture includes corresponding red, green, and blue sampling arrays. However, in video coding, each pixel is typically represented in a luminance/chrominance format or color space, e.g., YCbCr, comprising a luminance component (sometimes also indicated by L) indicated by Y and two chrominance components indicated by Cb and Cr. The luminance (luma) component Y represents the luminance or gray level intensity (e.g. both are the same in a gray scale 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 luminance sample array of luminance sample values (Y), and two chrominance sample arrays of chrominance 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 luminance 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 store, any type of (internal or external) interface that includes or stores previously captured or generated pictures, and/or obtains or receives pictures. The camera may be, for example, an integrated camera local or integrated in the source device, and the memory may be an integrated memory local or integrated in the source device, for example. The interface may be, for example, an external interface that receives pictures from an external video source, for example, an external picture capturing device such as a camera, an external memory, or an external picture generating device, for example, an external computer graphics processor, computer, or 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 for obtaining picture data 17 may be the same interface as communication interface 22 or part of communication interface 22.

Unlike pre-processing unit 18 and the processing performed by pre-processing unit 18, picture or picture data 17 (e.g., video data 16) may also be referred to as raw picture or raw picture data 17.

Pre-processing unit 18 is configured to receive (raw) picture data 17 and perform pre-processing on picture data 17 to obtain a pre-processed picture 19 or pre-processed picture data 19. For example, the pre-processing performed by pre-processing unit 18 may include trimming, color format conversion (e.g., from RGB to YCbCr), toning, or denoising. It is to be understood that the pre-processing unit 18 may be an optional component.

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

Communication interface 22 of source device 12 may be used to receive encoded picture data 21 and transmit to other devices, e.g., destination device 14 or any other device for storage or direct reconstruction, or to process encoded picture data 21 prior to correspondingly storing encoded data 13 and/or transmitting encoded data 13 to other devices, e.g., destination device 14 or any other device for decoding or storage.

Destination device 14 includes a decoder 30 (e.g., a video decoder 30), and may additionally, that is, optionally, include a communication interface or unit 28, a post-processing unit 32, and a display device 34.

Communication interface 28 of destination device 14 is used, for example, to receive encoded picture data 21 or encoded data 13 directly from source device 12 or any other source, such as a storage device, such as 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 by way of a direct communication link between source device 12 and destination device 14, such as a direct wired or wireless connection, or by way of 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.

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

Communication interface 28, which forms a corresponding part of communication interface 22, may for example be used to decapsulate encoded data 13 to obtain encoded picture data 21.

Both communication interface 22 and communication interface 28 may be configured as a unidirectional communication interface, as indicated by the arrow from source device 12 to destination device 14 for encoded picture data 13 in fig. 1A, or as a bidirectional communication interface, and may be used, for example, to send and receive messages to establish a connection, acknowledge and exchange any other information related to a communication link and/or a data transmission, e.g., an 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, the decoder 30 may be used to perform embodiments one through seven described below.

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

Display device 34 of destination device 14 is used to receive post-processed picture data 33 to display a picture to, for example, a user or viewer. Display device 34 may be or may include any type of display for presenting the reconstructed picture, such as an integrated or external display or monitor. For example, the display may include a Liquid Crystal Display (LCD), an Organic Light Emitting Diode (OLED) display, a plasma display, a projector, a micro LED display, a liquid crystal on silicon (LCoS), a Digital Light Processor (DLP), or any other display of any kind.

Although fig. 1A depicts source apparatus 12 and destination apparatus 14 as separate apparatuses, an apparatus embodiment may also include the functionality of both source apparatus 12 and destination apparatus 14 or both, i.e., source apparatus 12 or corresponding functionality and destination apparatus 14 or corresponding functionality. In such embodiments, source device 12 or corresponding functionality and 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 existence and (exact) division of the functionality of the different elements, or source device 12 and/or destination device 14 as 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 (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), 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 included in one or more encoders or decoders, either of which may be integrated as part of a combined encoder/decoder (codec) in a corresponding device.

Source device 12 may be referred to as a video encoding device or a video encoding apparatus. Destination device 14 may be referred to as a video decoding device or a video decoding apparatus. Source device 12 and 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, a mobile phone, a smart phone, a tablet or tablet computer, a camcorder, a desktop computer, a set-top box, a television, a display device, a digital media player, a video game console, a video streaming device (e.g., a content service server or a content distribution server), a broadcast receiver device, a 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, source device 12 and 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 application may be applicable to video encoding settings (e.g., video encoding or video decoding) that do not necessarily involve any data communication between the encoding and decoding devices. In other examples, the data may be retrieved from local storage, streamed over a network, and so on. A video encoding device may encode and store data to a memory, and/or a video decoding device may retrieve and decode data from a memory. In some examples, the encoding and decoding are performed by devices that do not communicate with each other, but merely encode data to and/or retrieve data from memory and decode data.

It should be understood 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. With respect to 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 instances, 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. 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, video encoder 20, video decoder 30 (and/or a video encoder implemented by logic 47 of processing unit 46), an antenna 42, one or more processors 43, one or more memories 44, and/or a display device 45.

As shown, the imaging device 41, the antenna 42, the processing unit 46, the logic circuit 47, the video encoder 20, the video decoder 30, the processor 43, the memory 44, and/or the 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. Display device 45 may be used to present video data. In some examples, logic 47 may be implemented by processing unit 46, as shown. The processing unit 46 may comprise application-specific integrated circuit (ASIC) logic, a graphics processor, a general-purpose processor, or the like. Video coding system 40 may also include an optional processor 43, which optional processor 43 similarly may include application-specific integrated circuit (ASIC) logic, a graphics processor, a general-purpose processor, or the like. In some examples, the logic 47 may be implemented in hardware, such as video encoding specific hardware, and the processor 43 may be implemented in general purpose software, an operating system, and so on. In addition, the Memory 44 may be any type of Memory, such as a volatile Memory (e.g., Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), etc.), a nonvolatile Memory (e.g., flash Memory, etc.), and the like. In a non-limiting example, storage 44 may be implemented by a speed cache memory. In some instances, logic circuitry 47 may access memory 44 (e.g., to implement an image buffer). In other examples, logic 47 and/or processing unit 46 may include memory (e.g., cache, etc.) for implementing image buffers, 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 circuitry 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, logic circuit implemented video decoder 30 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 circuitry 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 encoding partition (e.g., transform coefficients or quantized transform coefficients, (as discussed) optional indicators, and/or data defining the encoding partition). Video encoding system 40 may also include a video decoder 30 coupled to antenna 42 and configured to decode the encoded bitstream. The display device 45 is used to present video frames.

Encoder and 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. In the example of fig. 2, video encoder 20 includes a residual calculation unit 204, a transform processing unit 206, a quantization unit 208, an inverse quantization unit 210, an inverse transform processing unit 212, a reconstruction unit 214, a buffer 216, a loop filter unit 220, a Decoded Picture Buffer (DPB) 230, a prediction processing unit 260, and an entropy encoding unit 270. Prediction processing unit 260 may include inter prediction unit 244, intra prediction unit 254, and mode selection unit 262. 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, and, 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 (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 a signal path of a decoder (see the decoder 30 in fig. 3).

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

Segmentation

An embodiment of encoder 20 may include a partitioning unit (not shown in fig. 2) for partitioning picture 201 into a plurality of blocks, such as block 203, typically into a plurality of non-overlapping blocks. The partitioning unit may be used to use the same block size for all pictures in a 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 partition each picture into corresponding blocks.

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

Like picture 201, block 203 is also or can be viewed as a two-dimensional array or matrix of sample points having intensity values (sample values), although smaller in size than picture 201. In other words, the block 203 may comprise, for example, one sample array (e.g., a luma array in the case of a black and white picture 201) or three sample arrays (e.g., a luma array and two chroma arrays in the case of a color picture) 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., performing encoding and prediction for 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), e.g. by subtracting sample values of the picture block 203 from sample values of the prediction block 265 on a sample-by-sample (pixel-by-pixel) basis to obtain the residual block 205 in the sample domain.

Transformation of

The transform processing unit 206 is configured to apply a transform, such as a Discrete Cosine Transform (DCT) or a Discrete Sine Transform (DST), on the sample values of the residual block 205 to obtain transform coefficients 207 in a 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 transform specified for HEVC/h.265. Such integer approximations are typically scaled by some factor compared to the orthogonal DCT transform. To maintain the norm of the residual block processed by the forward transform and the inverse transform, an additional scaling factor is applied as part of the transform process. The scaling factor is typically selected based on certain constraints, e.g., the scaling factor is a power of 2 for a shift operation, a trade-off between bit depth of transform coefficients, accuracy and implementation cost, etc. For example, a specific scaling factor may be specified on the decoder 30 side for the inverse transform by, for example, inverse transform processing unit 212 (and on the encoder 20 side for the corresponding inverse transform by, for example, inverse transform processing unit 212), and correspondingly, a corresponding scaling factor may be specified on the encoder 20 side for the forward transform by transform processing unit 206.

Quantization

Quantization unit 208 is used to quantize transform coefficients 207, e.g., by applying scalar quantization or vector quantization, to obtain quantized transform coefficients 209. 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 transform coefficients 207. For example, an n-bit transform coefficient may be rounded down to an m-bit transform coefficient during quantization, where n is greater than m. The quantization level may be modified by adjusting a Quantization Parameter (QP). For example, for scalar quantization, different scales may be applied to achieve finer or coarser quantization. Smaller quantization steps correspond to finer quantization and larger quantization steps correspond to coarser quantization. An appropriate quantization step size may be indicated by a Quantization Parameter (QP). For example, the quantization parameter may be an index of a predefined set of suitable quantization step sizes. For example, a smaller quantization parameter may correspond to a fine quantization (smaller quantization step size) and a larger quantization parameter may correspond to a coarse quantization (larger quantization step size), or vice versa. The quantization may comprise a division by a quantization step size and a corresponding quantization or inverse quantization, e.g. performed by inverse quantization 210, or may comprise a multiplication by a quantization step size. Embodiments according to some standards, such as HEVC, may use a quantization parameter to determine the quantization step size. In general, the quantization step size may be calculated based on the quantization parameter using a fixed point approximation of an equation that includes division. Additional scaling factors may be introduced for quantization and dequantization to recover the norm of the residual block that may be modified due to the scale used in the fixed point approximation of the equation for the quantization step size and quantization parameter. In one example implementation, the inverse transform and inverse quantization 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 greater 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., to apply an inverse quantization scheme of the quantization scheme applied by the quantization unit 208 based on or using the same quantization step as the quantization unit 208. The dequantized coefficients 211 may also be referred to as dequantized residual coefficients 211, corresponding to transform coefficients 207, although the loss due to quantization is typically not the same as 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 (DCT) or an inverse 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 transform dequantized block 213 or an inverse transform residual block 213.

The reconstruction unit 214 (e.g., 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 (or simply "buffer" 216), such as a line buffer 216, is used to buffer or store the reconstructed block 215 and corresponding sample values, for example, for intra prediction. In other embodiments, the encoder may be used to use the unfiltered reconstructed block and/or corresponding sample values stored in buffer unit 216 for any class of estimation and/or prediction, such as intra prediction.

For example, an embodiment 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 filtered block 221 and/or blocks or samples from decoded picture buffer 230 (neither shown in fig. 2) as input or basis for 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, so as to facilitate pixel transition or improve video quality. Loop filter unit 220 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 (ALF), or a sharpening or smoothing filter, or a collaborative filter. 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. The decoded picture buffer 230 may store the reconstructed encoded block after the loop filter unit 220 performs a filtering operation on the reconstructed encoded block.

Embodiments of encoder 20 (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 (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 from any of a variety of memory devices, such as Dynamic Random Access Memory (DRAM) (including synchronous DRAM)

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

Prediction processing unit 260, also referred to as block prediction processing unit 260, is used to receive or obtain block 203 (current block 203 of current picture 201) and reconstructed picture 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 prediction block 265, which may be inter-predicted block 245 or intra-predicted 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 prediction modes (e.g., from those supported by prediction processing unit 260) that provide the best match or the smallest residual (smallest residual means better compression in transmission or storage), or that provide the smallest signaling overhead (smallest signaling overhead means better compression in transmission or storage), or both. The mode selection unit 262 may be configured to determine a prediction mode based on Rate Distortion Optimization (RDO), i.e., select a prediction mode that provides the minimum rate distortion optimization, or select a prediction mode in which the associated rate distortion at least meets the prediction mode selection criteria.

The prediction processing performed by the example of the encoder 20 (e.g., by the prediction processing unit 260) and the mode selection performed (e.g., by the 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 set of (predetermined) prediction modes. The prediction mode set may include, for example, intra prediction modes and/or inter prediction modes.

The intra prediction mode set may include 35 different intra prediction modes, or may include 67 different intra prediction modes, or may include an intra prediction mode defined in h.266 under development.

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

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

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

The inter prediction unit 244 may include a Motion Estimation (ME) unit (not shown in fig. 2) and a Motion Compensation (MC) unit (not shown in fig. 2). The motion estimation unit is used to receive or obtain picture block 203 (current picture block 203 of current picture 201) and 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 comprise 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 forming the video sequence.

For example, the encoder 20 may be configured to select a reference block from a plurality of reference blocks of the same or different one 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 the current block to a motion estimation unit (not shown in fig. 2) as an inter prediction parameter. This offset is also called a Motion Vector (MV).

The motion compensation unit is used to obtain, e.g., 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 taking or generating a prediction block based on a motion/block vector determined by motion estimation (possibly performing interpolation to sub-pixel precision). Interpolation filtering may generate additional pixel samples from known pixel samples, potentially increasing the number of candidate prediction blocks that may be used to encode 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 in one reference picture list to which the motion vector points. Motion compensation unit 246 may also generate syntax elements associated with the blocks and video slices for use by video decoder 30 in decoding picture blocks of the video slices.

The intra prediction unit 254 is used to obtain, e.g., receive, the picture block 203 (current picture block) of the same picture and one or more previously reconstructed blocks, e.g., reconstructed neighboring blocks, for intra estimation. For example, encoder 20 may be used 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., an intra prediction mode that provides a prediction block 255 that is most similar to current picture block 203) or a minimum code rate distortion.

The intra-prediction unit 254 is further configured to determine the intra-prediction block 255 based on the intra-prediction parameters as the selected intra-prediction mode. In any case, after selecting the intra-prediction mode for the block, intra-prediction unit 254 is also used to provide intra-prediction parameters, i.e., information indicating the selected intra-prediction mode for the block, to 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.

Entropy encoding unit 270 is configured to apply an entropy encoding algorithm or scheme (e.g., a Variable Length Coding (VLC) scheme, a Context Adaptive VLC (CAVLC) scheme, an arithmetic coding scheme, a Context Adaptive Binary Arithmetic Coding (CABAC), syntax-based context-adaptive binary arithmetic coding (SBAC), Probability Interval Partition Entropy (PIPE) coding, or other entropy encoding methods or techniques) to individual or all of 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 output 272 in the form of, for example, 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 quantize the residual signal directly without the 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 the present application. Video decoder 30 is operative to receive encoded picture data (e.g., an encoded bitstream) 21, e.g., encoded by encoder 20, to obtain a 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 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), such as any or all of inter-prediction, intra-prediction parameters, loop filter parameters, and/or other syntax elements (decoded). The entropy decoding unit 304 is further for forwarding the inter-prediction parameters, the intra-prediction parameters, and/or other syntax elements to the prediction processing unit 360. Video decoder 30 may receive syntax elements at the video slice 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.

Prediction processing unit 360 may include inter prediction unit 344 and intra prediction unit 354, where inter prediction unit 344 may be functionally similar to inter prediction unit 244 and intra prediction unit 354 may be functionally similar to 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 (explicitly or implicitly) prediction related parameters and/or information about the selected prediction mode from, for example, the entropy decoding unit 304.

When the video slice is encoded as an intra-coded (I) slice, intra-prediction unit 354 of prediction processing unit 360 is used to generate a prediction block 365 for the picture block of the current video slice based on the signaled intra-prediction mode and data from previously decoded blocks of the current frame or picture. When a video frame is encoded as an inter-coded (i.e., B or P) slice, inter prediction unit 344 (e.g., a motion compensation unit) of prediction processing unit 360 is used to generate a prediction block 365 for the video block of the current video slice based on the motion vectors 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 the reference frame list using default construction techniques based on the reference pictures stored in DPB 330: list 0 and list 1.

Prediction processing unit 360 is used to determine prediction information for the video blocks of the current video slice by parsing the motion vectors and other syntax elements, and to generate a prediction block for the current video block being decoded using the prediction information. For example, prediction processing unit 360 uses some of the 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 a reference picture list of the slice, a motion vector for each inter-coded video block of the slice, an inter prediction state for each inter-coded 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 the video slice to determine the degree of quantization that should be applied and likewise the degree of inverse quantization that should be applied.

Inverse transform processing unit 312 is used 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 produce a block of residuals in the pixel domain.

The reconstruction unit 314 (e.g., summer 314) is used to add the inverse transform block 313 (i.e., reconstructed residual block 313) to the prediction block 365 to obtain the 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 (either during or after the encoding cycle) is used to filter reconstructed block 315 to obtain filtered block 321 to facilitate 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 (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.

Decoded video block 321 in a given frame or picture is then stored in decoded picture buffer 330, which stores reference pictures for subsequent motion compensation.

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

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

Fig. 4 is a schematic structural diagram of a video coding apparatus 400 (e.g., a video encoding apparatus 400 or a video decoding apparatus 400) according to an embodiment of the present invention. Video coding apparatus 400 is suitable for implementing 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.

Video coding apparatus 400 includes: an ingress port 410 and a reception 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. Video coding device 400 may also include optical-to-Electrical (EO) components and optical-to-electrical (opto) components coupled with ingress port 410, receiver unit 420, transmitter unit 440, and egress port 450 for egress or ingress of optical or electrical signals.

The processor 430 is implemented by 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. Processor 430 includes a coding module 470 (e.g., encoding module 470 or 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. Accordingly, substantial improvements are provided to the functionality of the video coding apparatus 400 by the encoding/decoding module 470 and affect the transition of the video coding apparatus 400 to different states. Alternatively, the encode/decode module 470 is implemented as instructions stored in the memory 460 and executed by the processor 430.

The memory 460, which may include one or more disks, tape drives, and solid state drives, may be used as an over-flow data storage device for storing programs when such programs are selectively executed, and for storing instructions and data that are read during program execution. The 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 source device 12 and 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 including multiple computing devices, or a single computing device such as a mobile phone, tablet computer, laptop computer, notebook computer, desktop computer, or the like.

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

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

Device 500 may also include one or more output apparatuses, such as a display 518. In one example, display 518 may be a touch-sensitive display that combines a display and a touch-sensitive element operable to sense touch inputs. A display 518 may be coupled to the processor 502 via the bus 512. Other output devices that permit a user to program apparatus 500 or otherwise use apparatus 500 may be provided in addition to display 518, or other output devices may be provided as an alternative to display 518. When the output device is or includes a display, the display may be implemented in different ways, including by a Liquid Crystal Display (LCD), a Cathode Ray Tube (CRT) display, a plasma display, or a 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 or later developed that can sense an image, such as an image of a user running 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 image sensing device 520 may be configured such that its field of view includes an area proximate display 518 and 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 known or later developed that can sense sound in the vicinity of the apparatus 500. The sound sensing device 522 may be positioned to face directly the user operating the apparatus 500 and may be used to receive sounds, such as speech or other utterances, emitted by the user while operating the apparatus 500.

Although the processor 502 and 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 multiple directly couplable machines (each machine having one or more processors), or distributed in a local area or other network. Memory 504 may be distributed among multiple machines, such as a network-based memory or a memory among multiple machines running apparatus 500. Although only a single bus is depicted here, the bus 512 of the device 500 may be formed from multiple buses. Further, the secondary memory 514 may be directly coupled to other components of the apparatus 500 or may be accessible over a network and may comprise a single integrated unit, such as one memory card, or multiple units, such as multiple memory cards. Accordingly, 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 a luminance (Y) component. Therefore, in addition to encoding the luminance component, the chrominance component needs to be encoded. There are generally YUV4:4:4, YUV4:2:2, and YUV4:2:0, according to the sampling method of the luminance component and the chrominance component in color video. As shown in fig. 6, where the crosses represent luminance component sampling points and the circles represent chrominance component sampling points.

4:4:4 Format: indicating that the chrominance components have not been downsampled;

4:2:2 Format: indicating that the chrominance components are down-sampled 2:1 horizontally relative to the luminance components and not vertically. For every two U sampling points or V sampling points, each row comprises four Y sampling points;

4:2:0 Format: representing a 2:1 horizontal down-sampling of the chrominance components relative to the luminance components, and a 2:1 vertical down-sampling.

Of these, YUV4:2:0 is most common. In the case of a video image in YUV4:2:0 sampling format, if the luminance component of an image block is a 2Mx2N sized image block, the chrominance component of the image block is an MxN sized image block. Hence, the chroma components of an image block are also referred to in this application as chroma blocks or chroma component blocks. This application is described in YUV4:2:0, but may be applied to other sampling methods for luminance and chrominance components.

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

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

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

pred_C(i，j)＝α*rec_L'(i，j)+β (1)

wherein α is the linear model coefficient, pred_C(i, j) is (i, j)) Prediction value, rec, of the chrominance pixel at the position_L' (i, j) is the luma reconstructed pixel value at the (i, j) position after the down-sampling of the luma reconstructed block corresponding to the current chroma block (hereinafter, simply referred to as the corresponding luma block) to the chroma component resolution. In the YUV4:2:0 format video, the resolution of the luminance component is 4 times (two times each width and height) the resolution of the chrominance component, and in order to obtain a luminance block having the same resolution as the chrominance block, the luminance component needs to be down-sampled to the chrominance resolution by the same down-sampling method as the chrominance component and then used.

The linear model coefficients do not need to be transmitted encoded, but are derived α using the edge pixels of the neighboring reconstructed blocks of the current chroma block and the luma component pixels at the corresponding positions of the edge pixels, as in fig. 7, an embodiment of Cross Component Prediction (CCP) is shown in fig. 7, rec_LFor the reconstructed luma block (the current chroma block corresponds to the luma block and the neighboring reference pixels), rec_L' is the downsampled luminance block, rec_C' are neighboring reconstructed reference pixels of the current chroma block. The size of the current chroma block is WxH, the neighboring reconstructed pixels on the upper and left sides of the current chroma block are used as reference pixels, the size of the corresponding luma block is 2Wx2H, and the luma block reference pixels are downsampled to chroma resolution, so as to obtain the pixel block shown in fig. 7 (b). The adjacent reference pixels in fig. 7(b) and 7(c) form a one-to-one correspondence relationship.

For convenience of explanation, the present application refers to adjacent upper and left sides for calculating linear model coefficients as templates (templates). The adjacent upper edge is called the upper template, and the adjacent left edge is called the left template. The chrominance sampling points in the upper template are called upper template chrominance points, the luminance sampling points in the upper template are called upper template luminance points, and the left template chrominance points and the left template luminance points are known similarly. The template brightness points and the template chroma points are in one-to-one correspondence, and the values of the sampling points form value pairs.

In the embodiment of the present application, the template represents a set of luminance points or chrominance points used for calculating coefficients of the linear model, wherein the luminance points generally need to be obtained by downsampling (since the resolution of luminance components is different from that of chrominance), and are denoted as Luma' samples. Chroma points (Chroma samples) are generally one or two rows of adjacent upper pixels and one or two columns of adjacent left pixels of a current Chroma block. Fig. 8(a) is a schematic diagram of the stencil using one row and one column, and fig. 8(b) is a schematic diagram of the stencil using two rows and two columns.

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

In addition, there are Multiple Model Linear Models (MMLM) modes, there are Multiple α and β, taking two linear models as an example, there are two sets of linear model coefficients, α₁，β₁And α₂，β₂. The MMLM uses the reconstructed luma component to derive the current chroma block prediction value according to a linear model, which may be expressed as:

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

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

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

A mode in which linear model coefficient calculation is performed using only the upper template may be referred to as an LMA (may also be referred to as an LMT) mode, and a mode in which linear model coefficient calculation is performed using only the left template may be referred to as an LML mode.

In a specific encoding process, the current chroma block selects the best mode from the LM mode and other chroma modes using the RDO criterion. 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 derivation method for reducing LM complexity. Specifically, the template luminance points and the corresponding chrominance points are divided into two classes (sets) according to the mean value of the template luminance points, and the two classes respectively calculate the luminance mean value and the chrominance mean value in the classes. And obtaining a linear model coefficient based on the two luminance mean values and the two chrominance mean values.

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

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

For convenience of description, let the value pair set of the template luminance point value and the template chrominance point value be Ω, the set of the template luminance point value be Ψ, and the set of the template chrominance point value be Φ.

Ω＝{(L₀，C₀)，(L₁，C₂)...(L_n，C_n)...(L_N-1，C_N-1)}

Ψ＝{L₀，L₁，...L_n，...L_N-1}

Φ＝{C₀，C₁，...C_n，...C_N-1}

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

The prediction method of the chroma block is described with reference to the following first to second embodiments. In particular, the following embodiments one through two may be performed by the system or device of the embodiment of FIGS. 1A-5.

Example one

As shown in fig. 10 at 1000, the mean of the template luminance points is first obtained, and then the template luminance points are divided into two sets according to whether they are larger than this mean. 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 a brightness mean value and a chroma mean value in each set, and deriving a linear model coefficient based on the two brightness mean values and the chroma mean value for predicting the chroma blocks. The embodiment one can be realized 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 embodiment shown in fig. 1A to 5. As described in detail below.

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

Here, the range of the template is a template region of the luminance block corresponding to the current chrominance block, and the template region includes an upper template and/or a left template, which may be described with reference to fig. 7 to 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, 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 luminance points is L_mean，Ψ＝{L₀，L₁，...L_n，...L_N-1}，

Then

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

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

Specifically, the template brightness point may be determined as whether it is greater than L_meanInto two sets, Ψ_LThe number of points in is S, Ψ_RThe number of points in (1) is T. Satisfy S + T ═ N. Ψ ═ Ψ_L+Ψ_R。

Ψ_L＝{L_i0,L_i1,L_i2,L_is,...L_iS},Ψ_LInner brightness value L_is≤L_mean；

Ψ_R＝{L_j0,L_j1,L_j2,L_jt,...L_jT},Ψ_RInner brightness value L_jt＞L_mean；

Here, is, jt ∈ [0, N-1 ].

In another embodiment of the present invention, the substrate is,

Ψ_L＝{L_i0,L_i1,L_i2,L_is,...L_iS},Ψ_Linner brightness value L_is＜L_mean；

Ψ_R＝{L_j0,L_j1,L_j2,L_jt,...L_jT},Ψ_RInner brightness value L_jt≥L_mean；

Here, is, jt ∈ [0, N-1 ].

That is, if the luminance points in the luminance block template include the luminance points corresponding to the average valueA brightness point, the brightness point corresponding to the mean value is located in the first brightness set Ψ_LOr at said second set of luminances Ψ_R. If there are a plurality of luminance points corresponding to the mean 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.

Because the template brightness points and the template chroma points are in one-to-one correspondence, the template chroma points are correspondingly divided into two sets phi ═ phi_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 mean value according to the value of the luminance point in the first luminance set, 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.

Specifically, if the first luminance mean value is L_LmeanThe first chroma mean value is C_LmeanThen, then

Wherein L is_isIs the value of the ith luminance point, C_isIs the value of the ith chromaticity point, is more than or equal to 0 and less than or equal to S-1, is in the range of 0, N-1]L_is≤L_meanOr L is_is＜L_mean. Taking fig. 11 as an example, pixel a is determined, and the chromatic value of pixel a is C_LmeanA brightness value of L_Lmean。

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

Specifically, if the second luminance average value is L_RmeanThe second chroma mean value is C_RmeanThen, then

Wherein L is_jtIs the value of the jth luminance point, C_jtIs the value of jth chromaticity point, jt is more than or equal to 0 and less than or equal to T-1, and jt belongs to [0, N-1]]L_jt＞L_meanOr L_jt≥L_mean. Taking fig. 11 as an example, pixel B is determined, and the chromatic value of pixel B is C_RmeanA brightness value of L_Rmean。

Steps

1006 and 1008 do not have a precedence order.

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

In particular based on L_Lmean，L_Rmean,C_Lmean,C_RmeanLinear model coefficients α and β are obtained.

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

β＝C_mean-α*L_mean

here, the first and second liquid crystal display panels are,

where N is the number of chroma points in the chroma block template, C_nIs the value of the nth chromaticity point, N is more than or equal to 0 and less than or equal to N-1.

Step 1012, obtaining a prediction value of the 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, a prediction value of a chrominance point of a chrominance block may be obtained with reference to equation (1).

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

Example two

In the second embodiment, compared to the first embodiment, two linear models are obtained by using classification and class mean methods. Firstly, the luminance points are divided into two categories according to the average value of the template luminance points, and the corresponding chrominance points are also divided into two categories. And each class derives linear model coefficients by using the method in the first embodiment to obtain two linear models. And then obtaining a predicted value of the chroma block by adopting a formula (2) based on the two linear models.

The prediction method of the chroma block is described in conjunction with 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 mean value according to the values of the brightness points in the first brightness set.

Specifically, if the first luminance mean value is L_LmeanThen, then

Wherein L is_isIs the value of the is-th brightness point, 0 ≦ is ≦ S-1,is∈[0，N-1]L_is≤L_meanOr L is_is＜L_mean。

And 1208, obtaining a second brightness mean value according to the values of the brightness points in the second brightness set.

Specifically, if the second luminance average value is L_RmeanThen, then

Wherein L is_jtIs the value of the jth brightness point, jt is more than or equal to 0 and less than or equal to T-1, and jt belongs to [0, N-1]]L_jt＞L_meanOr L_jt≥L_mean。

Steps

1206 and 1208 do not succeed one another.

The method of embodiment one is then performed separately for the first and second luminance sets. The specific description is as follows.

Step 1302, dividing the brightness points in the first brightness set into two brightness sets, where the value of the brightness point in the third brightness set is smaller than the first brightness mean value, and the value of the brightness point in the fourth brightness set is larger than the first brightness mean value.

In particular, the first luminance set may be determined as to whether it is greater than the first luminance mean value L_LmeanInto two sets Ψ_LLAnd Ψ_LR。

Ψ_LL＝{L_e0,L_e1,L_e2,L_ew,...L_eW},Ψ_LLInner brightness value L_ew≤L_Lmean；

Ψ_LR＝{L_f0,L_f1,L_f2,L_fv,...L_fV},Ψ_LRInner brightness value L_fv＞L_Lmean；

Here, W + V is S.

In another embodiment of the present invention, the substrate is,

Ψ_LL＝{L_e0,L_e1,L_e2,L_ew,...L_eW},Ψ_LLinner brightness value L_ew＜L_Lmean；

Ψ_LR＝{L_f0,L_f1,L_f2,L_fv,...L_fV},Φ_LRInner brightness value L_fv≥L_Lmean；

Because the template brightness points and the template chromaticity points are in one-to-one correspondence, the template chromaticity points are correspondingly divided into two sets to correspondingly obtain a chromaticity point subset:

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 at 1004.

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

Specifically, if the third luminance average value is L_LLmeanThe third chroma mean value is C_LLmeanThen, then

Taking fig. 13 as an example, the A1 pixel is determined, and the chroma value of the A1 pixel is C_LLmeanA brightness value of L_LLmean。

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

Similarly, a fourth luminance mean value of L is obtained_LRmeanAnd the fourth chroma mean value is C_LRmean。

Taking FIG. 13 as an example, the B1 pixel and the B1 pixel are determinedA chromaticity value of C_LRmeanA brightness value of L_LRmean。

Reference is made specifically to the description of 1008.

Step 1308, a first group of linear model coefficients is obtained according to the third luminance average value, the third chrominance average value, the fourth luminance average value and the fourth chrominance average value.

Specifically, the third luminance mean value is L_LLmeanThe third chroma mean value is C_LLmeanThe fourth luminance mean value is L_LRmeanThe fourth chroma mean value is C_LRmeanThen the first set of linear model coefficients α₁And β₁Is composed of

In another embodiment, β₁Or on the basis of the mean value L of the pixel values in the first luminance set_LmeanAnd the mean value C of the pixel values in the first chrominance set_LmeanAnd (3) calculating:

β₁＝C_Lmean-α₁*L_Lmean

wherein

，C_isIs the value of the ith chromaticity point, is more than or equal to 0 and less than or equal to S-1, is in the range of 0, N-1]。

Steps 1402-1408 are similar to steps 1302-1308 and have no precedence order.

Step 1402, dividing the brightness points in the second brightness set into two brightness sets, where the value of the brightness point in the fifth brightness set is smaller than the second brightness mean value, and the value of the brightness point in the sixth brightness set is larger than the second brightness mean value.

In particular, the second set of luminances may be determined as to whether or not it is greater than the second luminance mean value L_RmeanInto two sets Ψ_RLAnd Ψ_RR。

Ψ_RL＝{L_g0,L_g1,L_g2,L_gm,...L_gM},Ψ_RLInner brightness value L_gm≤L_Rmean；

Ψ_RR＝{L_h0,L_h1,L_h2,L_hk,...L_hK},Ψ_RRInner brightness value L_hk＞L_Rmean；

Here, M + K ═ T.

In another embodiment of the present invention, the substrate is,

Ψ_RL＝{L_g0,L_g1,L_g2,L_gm,...L_gM},Ψ_RLinner brightness value L_gm＜L_Rmean；

Ψ_RR＝{L_h0,L_h1,L_h2,L_hk,...L_hK},Ψ_RRInner brightness value L_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 at 1004.

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

Similarly, a fifth luminance mean value L may be obtained_RLmeanFifth color mean value C_RLmean。

Taking fig. 13 as an example, the A2 pixel is determined, and the chroma value of the A2 pixel is C_RLmeanA brightness value of L_RLmean。

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

Similarly, a sixth luminance mean value L may be obtained_RRmeanThe sixth chroma mean value is C_RRmean。

Taking fig. 13 as an example, the B2 pixel is determined, and the chrominance value of the B2 pixel is C_RRmeanA brightness value of L_RRmean。

Reference is made specifically to the description of 1008.

Step 1408, obtaining a second group of linear model coefficients according to the fifth luminance average value, the fifth chrominance average value, the sixth luminance average value and the sixth chrominance average value.

Specifically, the fifth luminance mean value is L_RLmeanThe fifth chroma mean value is C_RLmeanThe sixth luminance mean value is L_RRmeanThe sixth chroma mean value is C_RRmeanThen the second three sets of linear model coefficients α₂，β₂Is composed of

In another embodiment, β₂Or on the basis of the mean value L of the pixel values in the second set of luminances_RmeanAnd the mean value C of the pixel values in the second chrominance set_RmeanAnd (3) calculating:

β₂＝C_Rmean-α₂*L_Rmean

wherein

，

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

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

Specifically, a prediction value of the current chroma block is obtained according to formula (2) after the reconstructed value of the luma block.

In other embodiments, the third set of luminances may be subdivided into two or more sets of luminances based on the third mean value of luminances. Similarly, the fourth, fifth, and sixth luminance sets may be subdivided into two or more luminance sets.

Compared with the prior art that the two linear models are obtained based on the least square method, the method in the second embodiment of the invention can reduce the complexity of the linear models, thereby improving the efficiency of chroma encoding and decoding.

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

β＝C_mean-α*L_mean

here, C is mentioned_meanAnd L_meanCalculation of values, for MDLM, LMA will calculate these two means directly using the sample value in the upper template, LML will calculate these two means directly using the sample value in the left template. Examples three to five are described in detail.

EXAMPLE III

The third embodiment is to obtain the prediction 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 sample points and H1 is the number of left template sample points. Here, W1> -W and H1> -H.

For the LMT mode, to obtain the average value for calculating β, the sampling points of the part a1 are used, and the length of the part a1 is W.

For the LML mode, to obtain the average value for calculating β, sampling points of the L1 part are used, and the length of the L1 part is H.

In addition, when calculating the average value, the number of sampling points may be reduced by using a sampling step length method. The sampling step size may be 2,4,8 …

Example four

The fourth embodiment is to obtain the prediction 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, W1 is the number of upper template sample points and H1 is the number of left template sample points, as shown in fig. 15. Here, W1> -W and H1> -H.

For the LMT mode, in order to obtain the average value for calculating β, sampling points at the right side portions of a2 (upper right) and a1 (upper right), and the lengths of the right side portions of a2 and a1 are W, in this embodiment, W sampling points are obtained from sampling points of the upper template to calculate the average value of the luminance points in the luminance block template, wherein sampling points in a2 are all available (available), if the width of a2 is W, the average value of the luminance points in the luminance block template is calculated using only the sampling points in a2, and if the width of a2 is less than W, the pixel at the right side of a2 is unavailable (un-available), for example, W luminance points include an adjacent pixel point a2 at the upper right of the luminance block, or W luminance points include an adjacent pixel point a1 above the luminance block and an adjacent pixel point a2 at the upper right of the luminance block.

For the LML mode, in order to obtain the average value for calculating β, sampling points at the lower side portions of L2 (lower left) and L1 (lower left), and the lengths of the lower side portions of L2 and L1 are H, in this embodiment, H sampling points are obtained from left template sampling points to calculate the average value of the luminance points in the luminance block template, wherein the sampling points in L2 are all available (available), if the length of L2 is H, the average value of the luminance points in the luminance block template is calculated using only the sampling points in L2, and if the length of L2 is less than H, the pixel at the lower side of L2 is not available (un-available), for example, H luminance points include an adjacent pixel point L2 at the lower left of the luminance block, or H luminance points include an adjacent pixel point L1 at the left of the luminance block and an adjacent pixel point L2 at the lower left of the luminance block.

EXAMPLE five

When the number of pixel points samples in the top or left template is not a power of 2, the mean value used for calculation β can be obtained by using a shift operation, and a division operation caused by the need to calculate the mean value is avoided.

For the LMT mode, to get the mean value for calculation β, as shown in FIG. 16, sample points for the A1, A2, and A3 portions may be used, the length of these three portions being W2, W2 being a power of 2 and being a minimum not less than W1. the A3 portion is obtained by a padding (padding) operation, for example, copying the rightmost pixel value of the A2 portion^kThe brightness point obtains the average value of the brightness points in the brightness block template, k is a natural number, wherein 2^kNot less than W1, and taking the minimum value.

For the LML mode, to obtain the mean value for computing β, sample points are used for the L1, L2 and L3 portions, which have a length of H2 and H2 is a power of 2 value and is a minimum value not less than H1, the L3 portion is obtained by padding operation, for example, copying the pixel value of the lowest side of the L2 portion^kThe brightness point obtains the average value of the brightness points in the brightness block template, k is a natural number, wherein 2^kNot less than H1, and taking the minimum value.

In the third to fifth embodiments of the present invention, the number of luminance points in the luminance block template used when obtaining the average value is limited, so that the efficiency of chrominance encoding and decoding can be further improved.

It should be understood that the disclosure in connection with the described methods may equally apply to the corresponding apparatus or system for performing the methods, and vice versa. For example, if one or more particular method steps are described, the corresponding apparatus may comprise one or more units, such as functional units, to perform the described one or more method steps (e.g., a unit performs one or more steps, or multiple units, each of which performs 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, for example, if a particular apparatus is described based on one or more units, such as functional units, the corresponding method may comprise one step to perform the functionality of the one or more units (e.g., one step performs the functionality of the one or more units, or multiple steps, each of which performs the functionality of one or more of the plurality of 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. Computer readable media may comprise computer readable storage media corresponding to tangible media, such as data storage media or communication media, including any medium that facilitates transfer of a computer program from one place to another, such as according to a communication protocol. In this manner, the computer-readable medium may generally correspond to (1) a non-transitory tangible computer-readable storage medium, or (2) a communication medium, e.g., a signal or carrier wave. A data storage medium may be any available medium 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 instructions are transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, 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 instead directed to non-transitory tangible storage media. Disk and disc, as used herein, includes Compact Disc (CD), laser disc, optical 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 (DSPs), general purpose microprocessors, Application Specific Integrated Circuits (ASICs), 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. In addition, 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 composite 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 (IC), or a collection of ICs (e.g., a chipset). This disclosure describes various components, modules, or units to emphasize functional aspects of the apparatus for performing the disclosed techniques, but does not necessarily require realization by different hardware units. Specifically, as described above, the various units may be combined in a codec hardware unit, or provided by a collection of interoperative hardware units, including one or more processors as described above, in conjunction with suitable software and/or firmware.

Claims

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

obtaining a mean value of luminance points in a luminance block template, wherein the luminance block corresponds to the chrominance 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 mean 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 mean value of the brightness points in the brightness block template;

obtaining a first brightness mean value according to the values 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 mean value according to the values of the brightness points in the second brightness set;

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

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

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

2. The method according to claim 1, wherein if the luminance points in the luminance block template include the luminance point corresponding to the mean value, the luminance point corresponding to the mean value is located in the first luminance set or located 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 prediction 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 comprises: and obtaining a predicted value of the chrominance point of the chrominance block according to the value of the luminance point of the luminance block, the second group of linear model coefficients and the third group of linear model coefficients.

4. The method of claim 3, further comprising:

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

obtaining a third brightness mean value according to the values of the brightness points in the third brightness set;

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

obtaining a fourth brightness mean value according to the values of the brightness points in the fourth brightness set;

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

and obtaining the second group of linear model coefficients according to the third brightness mean value, the third chroma mean value, the fourth brightness mean value and the fourth chroma mean 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 point in the fifth brightness set is smaller than the second brightness mean value, and the value of the brightness point in the sixth brightness set is larger than the second brightness mean value;

obtaining a fifth brightness mean value according to the values of the brightness points in the fifth brightness set;

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

obtaining a sixth brightness mean value according to the values of the brightness points in the sixth brightness set;

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

and obtaining the third group of linear model coefficients according to the fifth brightness mean value, the fifth chroma mean value, the sixth brightness mean value and the sixth chroma mean value.

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

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

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

9. The method of claim 8, wherein 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 chrominance 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 luma points comprise a neighboring pixel point to the left of the luma block and a neighboring pixel point to the left of the luma block.

11. Method according to any of claims 8-10, wherein the prediction method is a multidirectional linear model, MDLM, mode prediction method, wherein the MDLM mode is an LMA mode.

12. The method according to any one of claims 1-7, wherein the luminance points in the luminance block template comprise pixels of an upper row or upper rows adjacent to the luminance block.

13. The method of claim 12, wherein 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 chrominance 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 luma points comprise a top-adjacent pixel point of the luma block and a top-right adjacent pixel point of the luma block.

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

16. According to the rightThe method of claim 8 or 12, wherein the method comprises: by using 2^kThe brightness point obtains the average value of the brightness points in the brightness block template, k is a natural number, wherein 2^kNot less than the total number of luminance points in the luminance block template.

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

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

19. The method according to any one of claims 1-18, wherein the first luminance mean value is L_LmeanThe first chroma mean value is C_LmeanThe second brightness mean value is L_RmeanThe second chroma mean value is C_RmeanThen the first set of linear model coefficients α and β are:

20. the method according to any one of claims 1-18, wherein the mean value of the luminance points in the luminance block template is L_meanThe mean value of the chrominance points in the chrominance block template is C_meanThe first brightness mean value is L_LmeanThe first chroma mean value is C_LmeanThe second brightness mean value is L_RmeanThe second chroma mean value is C_RmeanThen the first set of linear model coefficients α and β are:

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

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

0≤n≤N-1。

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

Wherein N is the number of chroma points in the chroma block template, C_nIs the value of the nth chromaticity point, N is more than or equal to 0 and less than or equal to N-1.

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

wherein the mean value of the brightness points in the brightness block template is L_mean，L_isIs the value of the ith brightness point, is more than or equal to 0 and less than or equal to S-1, L_is≤L_meanOr L_is＜L_mean。

24. The method of claim 23, wherein the first color mean C_LmeanComprises the following steps:

wherein C is_isIs 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 according to any one of claims 1-24, wherein the number of luminance points in the second luminance set is T, and the second luminance mean value L is_RmeanComprises the following steps:

wherein the mean value of the brightness points in the brightness block template is L_meanWherein L is_jtIs the value of the jth luminance point, L_jt＞L_meanOr L_jt≥L_mean，0≤jt≤T-1。

26. The method of claim 25, wherein the second chrominance mean C_RmeanComprises the following steps:

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

27. The method of claim 4, wherein the third luminance mean value is L_LLmeanThe third chroma mean value is C_LLmeanThe fourth luminance mean value is L_LRmeanThe fourth chroma mean value is C_LRmeanThen the second set of linear model coefficients α₁And β₁Is composed of

28. The method of claim 4, wherein the first luminance mean value is L_LmeanThe first chroma mean value is C_LmeanThe third brightness mean value is L_LLmeanThe third chroma mean value is C_LLmeanThe fourth luminance mean value is L_LRmeanThe fourth chroma mean value is C_LRmeanThen the second set of linear model coefficients α₁And β₁Is composed of

29. The method of claim 5, wherein the fifth luminance mean value is L_RLmeanThe fifth chroma mean value is C_RLmeanThe sixth luminance mean value is L_RRmeanThe sixth chroma mean value is C_RRmeanThen the third set of linear model coefficients α₂And β₂Is composed of

30. The method of claim 5, wherein the second luminance mean value is L_RmeanThe second chroma mean value is C_RmeanThe fifth luminance mean value is L_RLmeanThe fifth chroma mean value is C_RLmeanThe sixth luminance mean value is L_RRmeanThe sixth chroma mean value is C_RRmeanThen the third set of linear model coefficients α₂And β₂Is composed of

31. The method of 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 of the 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 of the 1-30.

34. A decoding device, 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 device 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.