New pixel based approach for reverse play of MPEG video for streaming system

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In macroblock based architecture of MPEG video streaming system with backward playback support, the macroblocks of the frames are divided into two categories: Backward Macroblock (BMB) and Forward/Backward Macroblock (FBMB). The BMB and FBMB are processed differently. This approach reduces the network bandwidth and buffer size requirements. In this paper, we propose a pixel based approach that accesses less data from the server and hence further saves the network bandwidth and buffer requirement. The I- or P-frame (say, frame n−1) is reverse-predicted from the currently decoded frame (i.e., frame n) that is stored in the frame buffer at the client system. Using the motion vector information of frame n, the positions of its various pixels are found in the frame n−1 and their exact values are found using the prediction errors of the frame n by just subtracting them from their values in the frame n. Thus, most of the pixels of frame n−1 are predicted from the frame n. Experimental results show that on an average 93.4% of pixels in the previous I- or P-frame can be reverse-predicted from the current P-frame. The rest 6.6% unpredicted pixels are accumulated in the form of blocks and those blocks are requested from the server. We also propose new Block Identification Algorithms to identify different blocks of unpredicted pixels in an image. They are Maximum Height Minimum Width (MHMW), First Come First Serve (FCFS), Maximum Area (MA), and Biggest Block (BB) algorithms. The server processes the MPEG video stream and returns the desired blocks. We also discuss a FindBlock algorithm for extracting a small block of any frame from the MPEG video stream. Thus, only the motion vectors, prediction errors of frame n, and the unpredicted pixels of the frame n−1 need to be transmitted to the client system. This makes considerable saving in system resources.

论文关键词:Backward play,MPEG video,Pixel based approach,Reverse play,VCR functionality

论文评审过程:Received 11 September 2009, Accepted 26 June 2011, Available online 5 July 2011.

论文官网地址:https://doi.org/10.1016/j.image.2011.06.006