VLSI architecture for VQ problems such as real-time image coding. The encoding process applied is independent of the vector dimensions and does not perform any arithmetic operations. Each processing elements in the VLSI is a magnitude comparator So far, we have studied still image coding techniques and the standards there in. In this paper now going to explore the most challenging area in multimedia communication that is video storage and transmission. A wide range of emerging applications, such as conversational video like video telephone, video conferencing through wired and wireless medium; streaming video, such as video on demand; digital TV/HDTV broadcasting, image / video database services, CD/DVD storage etc, demand significant amount of data compensation. Today, the technology has reached a state of maturity with the availability of coding and compression tools, acceptance of international standards proposed by International Standards Organization (ISO)and International Telecommunications Union (ITU), but research is still on, to achieve further improvements..The decision tree generated by an offline process. Together with pipeline architecture, high speed encoding is now realizable in a single Chip. A new systolic architecture to realize the encoder of full-search vector quantization (VQ) for high-speed applications. The architecture possesses the features of regularity and modularity, and is thus very suitable for VLSI implementation. One major challenging sub band coding is efficiently coding sub bands, which have low energy, but contains important visual information. In this paper we used an efficient selection and coding of edge information in sub band transform domain for compression of high temporal sub bands .while maintaining their perceptual information. The rest of this paper is organized as follow. Section1 is discussing the first stage of our video coder which is a three dimensional filter bank, Section2 explains different encoding methods used for different sub bands, and in Section3,the whole block diagram of the proposed system with results of its implementation are explained. Finally Section4 summarize the works and concludes the paper

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Multiscale Edge Detection Vector quantisation