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Intra-frame prediction method and device for nonlinear texture and medium

An intra-frame prediction, nonlinear technology, applied in image communication, digital video signal modification, electrical components and other directions, can solve the problem of not being able to generate nonlinear texture content, and achieve the effect of reducing prediction residuals and improving coding efficiency

Active Publication Date: 2021-10-01
PEKING UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In order to solve the technical problem that the existing image and video coding standards cannot generate nonlinear texture content close to the original signal in the intra prediction module

Method used

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  • Intra-frame prediction method and device for nonlinear texture and medium
  • Intra-frame prediction method and device for nonlinear texture and medium
  • Intra-frame prediction method and device for nonlinear texture and medium

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Experimental program
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Embodiment 1

[0051] Such as figure 2 Shown:

[0052] The present disclosure provides an intra prediction method oriented to nonlinear texture, including:

[0053] Determine the current intra prediction mode;

[0054] predicting non-linear textures using predictive modeling involving quadratic functions in said intra prediction module;

[0055] The reference pixel is derived according to the result of predicting the nonlinear texture, and the predicted pixel value is generated according to the position of the reference pixel.

[0056] Further, the intra prediction mode specifically includes:

[0057] Normal prediction mode close to reference pixels and extended prediction mode far away from reference pixels.

[0058] Further, the predictive modeling is a model using a quadratic function or a model using a linear combination of a linear function and a quadratic function.

[0059] Further, the prediction of nonlinear texture using predictive modeling including quadratic function in the ...

Embodiment 2

[0099] The present disclosure can also provide a computer storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it is used to implement the steps of the above-mentioned intra prediction method oriented to nonlinear texture.

[0100] The computer storage medium of the present disclosure may be implemented using semiconductor memory, magnetic core memory, magnetic drum memory, or magnetic disk memory.

[0101] Semiconductor memory, mainly used in computers, mainly has two types of semiconductor memory elements: Mos and bipolar. Mos components are highly integrated, the process is simple but the speed is slow. Bipolar components are complex in process, high in power consumption, low in integration but fast in speed. After the advent of NMos and CMos, Mos memory began to play a major role in semiconductor memory. NMos is fast, for example, the access time of Intel's 1K-bit SRAM is 45ns. CMos consumes less power, and the...

Embodiment 3

[0107] The present disclosure also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and operable on the processor. When the processor executes the computer program, the above-mentioned intra prediction method oriented to nonlinear texture is realized. step.

[0108] Figure 4 It is a schematic diagram of the internal structure of the electronic device in one embodiment. Such as Figure 4 As shown, the electronic device includes a processor, a storage medium, a memory, and a network interface connected through a system bus. Wherein, the storage medium of the computer device stores an operating system, a database, and computer-readable instructions, and the database can store control information sequences. When the computer-readable instructions are executed by the processor, the processor can realize a non-linear Intra prediction method for textures. The processor of the electrical device is used to provide computin...

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Abstract

The invention relates to a nonlinear texture-oriented intra-frame prediction method and device and a medium, the method is used in an intra-frame prediction module in the field of image and video coding, and the method comprises the following steps: determining a current intra-frame prediction mode; predicting a non-linear texture in the intra prediction module using a prediction model comprising a quadratic function; deriving a position of a reference pixel from a result of predicting the non-linear texture, and a predicted pixel value being interpolated from the reference pixel. According to the invention, the problem of efficient prediction modeling of an image and video coding and decoding standard intra-frame prediction module for nonlinear texture content is solved. According to the invention, the high-fidelity prediction signal close to the original signal can be generated, the prediction residual error is reduced, and the coding efficiency is improved.

Description

technical field [0001] The present disclosure relates to the technical field of intra-frame prediction, and more specifically, the present disclosure relates to an intra-frame prediction method, device and medium for nonlinear texture. Background technique [0002] In image and video coding, intra-frame prediction is mainly used to reduce the spatial redundancy of signals. Mainstream video codec standards (such as VVC, AVS3, etc.) define a series of intra prediction angle modes in the intra prediction module to generate prediction content. However, the current angle prediction mode can only generate linear textures, and cannot accurately and efficiently model nonlinear textures. Therefore, the present invention proposes a non-linear texture-oriented intra-frame prediction algorithm to improve the efficiency of intra-frame prediction and improve the coding efficiency. [0003] There are 67 types of intra prediction modes in VVC, including DC mode, Planar mode and other 65 a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N19/159H04N19/182
CPCH04N19/159H04N19/182
Inventor 马思伟林凯张嘉琪贾川民李俊儒王苫社
Owner PEKING UNIV
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