Visual pattern matching in motion estimation for object-based very low bit-rate coding using moment-preserving edge detection

This paper proposes an object-based coding method for very low bit-rate channels, using a method based on motion estimation with a block-based moment-preserving edge detector. In most existing object-based coding methods, only the global motion components are transmitted. However, the global motion prediction error is large, even after motion compensation using the discrete cosine transform (DCT), when images contain rapid moving objects and noise. Furthermore, the global motion-compensating method cannot result in small prediction error if the segmented objects consist of subobjects that move along different directions. The technique proposed in this paper involves segmenting moving objects from video sequences and representing objects compactly by visual-pattern approximations of the boundary. A visual pattern is obtained by detecting the line edge from a square block using the moment-preserving edge detector. Since high computational complexity is required for motion estimation using block matching, a fast block-matching method based on the visual patterns is proposed to reduce the burden of the overall coder complexity. Computer simulation results show that the proposed method gives good performance in terms of the subjective quality, the peak signal-to-noise ratio, and the compression ratio.