Video coding and decoding system based on dictionary learning and compressed sensing

Abstract

The invention relates to the field of video compressed sensing and image sparse representation, and discloses a video coding and decoding system based on compressed sensing. The video coding and decoding system based on compressed sensing is designed to make a wireless video sensing network have the advantages that the complexity and calculated amount of a coding terminal are small, the volume of data transmitted through a channel is small and a decoding terminal can carry out high-quality real-time video reconstruction. According to the technical scheme, the video coding and decoding system based on dictionary learning and compressed sensing mainly comprises the video coding terminal and the video decoding terminal, wherein the coding terminal is used for temporarily storing image pixel data of K frames, reducing the dimensionality of the image pixel data of the K frames and transmitting data after dimensionality reduction to the decoding terminal through a wireless transmitting module according to the compressed sensing theory, and the decoding terminal is used for decoding the K frames according to the compressed sensing reconstruction algorithm (namely, the improved NSL0 method), storing the K frames and finally forming a video through integration according to frame sequences and outputting the video. The video coding and decoding system based on compressed sensing is mainly applied to video compressed sensing and transmission.

Description

Technical field [0001] The present invention relates to the fields of video compressed sensing and image sparse representation, and in particular to a compressed sensing video coding and decoding system based on dictionary learning. Background technique [0002] The present invention is mainly aimed at some video application fields with limited resources at the encoding end, such as video surveillance, wireless video sensor networks and the like. Due to the limitations of the equipment and environment, this application field requires a low-complexity, low-power encoding end to ensure long-term stable work, and the receiving end can perform a large amount of data storage and complex decoding calculations. [0003] However, both the H.26X series and the MPEG series of traditional video coding technologies adopt a complex system structure at the encoding end and simple decoding end, that is, the encoding end uses inter-frame prediction, intra-frame prediction and discrete cosine trans...

AI Technical Summary

Problems solved by technology

[0003] However, no matter it is the traditional video coding technology of H.26X series or MPEG series, it adopts a complex system structure at the encoding end and a simple decoding end, that is, the encoding end uses inter-frame prediction, intra-frame prediction and discrete cosine transform (DCT) to remove Temporal and spatial redundancy for high compression efficiency, which makes the entire system very demanding on the computing power and memory capacity of the encoder, much higher than that of the decoder

Therefore, traditional video coding methods are not suitable for the above fields

Images