Distributed video coding and decoding methods based on classification of key frames of correlation noise model (CNM)

Abstract

The invention discloses distributed video coding and decoding methods based on classification of key frames of a correlation noise model (CNM). The coding method comprises the following steps of: (1) computing a residual frame; (2) calculating Laplace parameter values of transformation coefficient grades of frames, blocks and frequency bands, and establishing CNM parameter tables of the differentfrequency bands according to the Laplace parameter value of the transformation coefficient grade of the frequency bands; and (3) according to the value of the residual frame and the CNM, dividing a coding sequence into a high-speed motion sequence block, a medium-speed motion sequence block and a low-speed motion sequence block which are coded by adopting an intra-frame mode, an inverse motion vector estimation mode and a frame skipping mode respectively. The decoding method comprises an adaptive three-dimensional recursive search method and an adaptive overlapped block motion compensation method based on the classification of the key frames of the CNM. By the methods provided by the invention, the quality of side information in distributed video coding can be improved effectively, the problem of incorrect estimation of motion vectors in the distributed video coding can be solved more effectively in a situation of no increase of the computational complexity of a coding terminal, and the more accurate motion vectors can be obtained simultaneously.

Description

technical field [0001] The invention belongs to the technical field of video compression, in particular to a distributed video encoding and decoding method based on CNM key frame classification. Background technique [0002] Distributed video coding is a brand-new video coding mode. It is based on the Slepian-Wolf and Wyner-Ziv multi-source information coding theory. It uses intra-frame coding and inter-frame decoding to transfer the computational complexity from the encoding end to the decoding end. It has the characteristics of low encoder complexity, low power consumption at the encoding end, and good fault tolerance. It is especially suitable for some wireless video terminals (such as wireless video surveillance systems, video sensor networks, etc.) with limited computing power, memory capacity, and power consumption, and has developed rapidly in recent years with the growth of these new video applications stand up. [0003] It is generally considered that the side inf...

AI Technical Summary

Problems solved by technology

In the current distributed video coding, key frame coding is mainly realized by intra-frame coding, however, the frequent use of intra-frame coding significantly reduces the coding efficiency, resulting in inefficient side information and WZ frames

Images