Background Modeling and Coding of Surveillance Video with Variable Block Size

To satisfy the demand of high compression ratio of surveillance video,and to deal with the challenge both of the massive surveillance video streams and the limit of storage space,a block-based surveillance background modeling algorithm is proposed.Firstly,the coding unit is divided into blocks,and the size of block is increased according to the length of the training set.Then,the gradient of residual blocks is calculated to describe the edge features of moving objects.Finally,the background model is updated by block replacement classification detection and block boundary detection to determine whether the current block is a background block.Based on the background image generated by BSBM,a long reference coding inter-prediction strategy is proposed,and the constructed background image is used as the global reference image to further improve the coding performance.The test results on RD17.0platform show that in the low-delay application scenarios,the subjective quality of the background image generated by the BSBM algorithm is well,the average of BD-Rate gain for YUV components is19.7%,26.6%and26.4%respectively,which indicates that the coding performance improves significantly.