Abstract. Surveillance video system as an effective means of public safety widely appeared in people's life in recent years. Traditional video coding technology, the encoding process is complex, computation, and conflicts with hardware limitations of the monitoring system. This paper presents a kind method used to design and train redundant dictionary based on image region. Each frame is divided into same-sized area with equal blocks, then the image areas of the same position are put together as the training sample library of regional redundant dictionary. In this way, redundant dictionary compression results in the occupied volume can be reduce. On top of this dictionary, surveillance video compression coding algorithm based on the regional dictionary is designed and implemented. Experimental results show that the proposed algorithm can effectively improve the compression ratio of the algorithm.With the need for Social and public security and big data analysis, video surveillance system is increasingly applied to people's life [1] . Surveillance systems made of various cameras are lying over all positions of the society and provide services for people's safe life. According to IDC (Data Corporation International) research report estimates, the total amount of global data will reach 40ZB in 2020, among which the data of surveillance video is 5.8ZB. And China will account for 21%, which means that in 2020, China will have 1.2ZB (One billion and two hundred million TB) surveillance video data needed to be stored, transmitted and analyzed. Therefore, facing with massive surveillance video, considering the transmission and storage costs, we need to carry out new research and achieve a major breakthrough in surveillance video encoding and analysis technology, it is very necessary to research higher compression efficiency of surveillance video encoding technologies. This paper proposes a method for studying of balancing the redundant dictionary size and the overall algorithm of encoding effect. The way to reduce the volume of redundant dictionary can be found out by analysing the compression result. The redundancy of each image block in the way of training the dictionary itself can be reduced by improving the original training method. A redundant dictionary trained by a region which is as a simple formed by multiple unit image blocks is applied to all of the image block in the area. This method use of redundant information can reduce the number of redundant dictionary, improve the training efficiency further, and do not cause significant losses for the compression algorithm of encoding efficiency. This paper also proposes a algorithm that combined with surveillance video compression and coding algorithm based on key frame to build the public background of surveillance and use the redundant dictionary to sparse decomposition the background image block or the image block with the approximate background, then quantize and compress correspondingly, while the foreground image block is reserved separately. Decoding the fore...
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