Compression sensing video encoding and decoding method based on Gaussian mixture model (GMM)

Abstract

The invention brings forward a compression sensing video encoding and decoding method based on a Gaussian mixture model (GMM). First of all, modeling is performed on a compression sensing video by use of the GMM, based on this, a GMM lossy compression method based on a product quantizer is designed, and a compression sensing video encoder and decoder is brought forward. Time-domain redundancy of the compression sensing video is eliminated by use of a DPCM difference coding technology, data redundancy is further removed by use of algorithm encoding, and output code streams are obtained for storage and transmission. According to the invention, the modeling is carried out on the compression sensing video with a random feature by use of the GMM, and at the same time, the time-domain redundancy of the compression sensing video is eliminated, such that system energy and calculation resources can be reduced, and the compression efficiency is improved. The method provided by the invention can satisfy application environments having energy and calculation complexity restrictions on a video encoding system, such as wireless multimedia sensing networks, space video obtaining, mobile terminal video obtaining and the like.

Description

technical field [0001] The invention belongs to the field of video coding and decoding, and in particular relates to a compression sensing video coding and decoding method based on a Gaussian mixture model. Background technique [0002] The video coding and decoding technology based on compressed sensing has changed the way of traditional video coding and decoding - the system mode of complex coding end and simple decoding end greatly reduces the consumption of energy and computing resources at the coding end, and integrates this energy, computing The burden of resources is shifted to the decoding end with relatively abundant resources, which expands the application of video codec technology in multimedia sensor networks, spatial video acquisition, mobile terminal video acquisition and other fields. A traditional digital video capture system includes two cascaded modules: 1) a camera for capturing scene videos, and 2) a data encoding processor for reducing the amount of capt...

AI Technical Summary

Problems solved by technology

However, this system structure cannot meet the needs of some application scenarios

Firstly, in some application scenarios, the digital video codec system has limited computing resources and energy supply; secondly, in some application scenarios, the cost and complexity of the system increase greatly with the increase of video spatial and temporal resolution

To this end, the video acquisition and codec system based on compressed sensing technology solves these problems by combining the scene video sampling and data compression process. Complexity requirements, how to use the existing system framework, combined with the distribution characteristics of compressed sensing video, to achieve efficient acquisition and encoding and decoding of digital video has become a prominent problem in current system design

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