Preprint Article Version 1 This version is not peer-reviewed

A DCVS Reconstruction Algorithm for Mine Video Monitoring Image Based on Block Classification

Version 1 : Received: 12 July 2018 / Approved: 13 July 2018 / Online: 13 July 2018 (03:43:55 CEST)

How to cite: Zhao, X.; Shen, X.; Wang, K.; Li, W. A DCVS Reconstruction Algorithm for Mine Video Monitoring Image Based on Block Classification. Preprints 2018, 2018070222 (doi: 10.20944/preprints201807.0222.v1). Zhao, X.; Shen, X.; Wang, K.; Li, W. A DCVS Reconstruction Algorithm for Mine Video Monitoring Image Based on Block Classification. Preprints 2018, 2018070222 (doi: 10.20944/preprints201807.0222.v1).

Abstract

Aiming at the problems that large amount of video monitoring image data in underground coal mines leads to difficulties in transmission and storage, compressed sensing theory is introduced to encode and decode video images, and a new distributed video coding scheme is proposed. In order to obtain more sparse representation and more general applicability, a block-based adaptive sparse base scheme is proposed. For the acquisition of side information, fixed weight is usually used to synthesize side information and the correlation between different image blocks is neglected, a block-based classification weighted side information generation scheme is proposed. Experimental results show that the block-based classification codec scheme can make full use of inter-frame correlation. Under the appropriate sampling rate, the PSNR value of video reconstruction increases, which effectively improves the quality of video frame reconstruction.

Subject Areas

compressed sensing; distributed video codec; sparse representation; side information reconstruction

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