Self-adapting interlayer texture prediction method of H.264/SVC

Abstract

The invention discloses a self-adapting interlayer texture prediction method of H.264 / SVC. When every intra-frame slice of an enhancement layer of the current space is encoded, the method comprises the following steps: sixteen corresponding reference layer pixels are determined for each pixel of the current layer, and a two-dimensional Wiener filter is utilized for carrying out interpolation filtering on the sixteen corresponding reference layer pixels, so that interlayer texture predicted values corresponding to the pixels of the current layer can be obtained; and the coefficient of the two-dimensional Wiener filter is transmitted into a decoding terminal. Correspondingly, when every intra-frame slice of the enhancement layer of the current space is processed by the decoding terminal, theinterpolation filtering is carried out on the sixteen corresponding reference layer pixels corresponding to the each pixel of the current layer according to the filter coefficient sent by a coding terminal, and the interlayer texture predicted values of the pixels of the current layer can be obtained. The method can be applied to improve the performance of the interlayer texture prediction and SVC space hierarchical coding efficiency.

Description

technical field [0001] The invention relates to video compression coding technology, in particular to an H.264 / SVC adaptive inter-layer texture prediction method. Background technique [0002] Scalable Video Coding (SVC, Scalable Video Coding) is a technology emerging in the past 20 years to cope with the diversity of modern video transmission systems and terminals. Scalability means that the video bit stream can be selectively "discarded" according to certain rules, so as to adapt to different network conditions and terminal performance requirements. [0003] Currently, the latest SVC standard is formulated by the Joint Video Team (JVT) as an appendix G of the H.264 / AVC (Advanced Video Coding) standard, and is generally referred to as H.264 / SVC. In the following description, unless otherwise specified, SVC refers to H.264 / SVC. [0004] The characteristic of the SVC code stream is that it contains several sub-code streams, and some sub-code streams can be extracted accordi...

AI Technical Summary

Problems solved by technology

[0016] 1. Due to the spatial 2-dimensionality of the video signal, simple horizontal and vertical 1-dimensional filtering cannot fully cover the characteristics of the video signal in all 2-dimensional directions, so the interpolation effect in non-horizontal and non-vertical directions is not good;

[0017] 2. Due to the statistical non-stationarity of the video signal, the fixed filter design cannot obtain the optimal interpolation performance in any occasion;

[0018] 3. Due to the inevitable introduction of aliasing distortion in the process of video signal acquisition, aliasing distortion will seriously affect the performance of interpolation filtering

The low-pass filter does not have the ability to resist aliasing, so it will also cause insufficient texture prediction performance between layers

[0019] Due to the limited performance of the interpolation filter, it will directly affect the performance of inter-layer texture prediction, which will limit the coding efficiency of SVC

Therefore, there is still room for improvement and improvement in the inter-layer texture prediction technology in the current SVC standard

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