This paper introduces a new binary shapecoding technique called generalized predictive shape coding (GPSC) to encode the boundary of a visual object compactly by using a vertex-based approach. GPSC consists of a cont...
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This paper introduces a new binary shapecoding technique called generalized predictive shape coding (GPSC) to encode the boundary of a visual object compactly by using a vertex-based approach. GPSC consists of a contour pixel matching algorithm and a motion-compliant contour coding algorithm. The contour pixel matching algorithm utilizes the knowledge of previously decoded contours by using a uniform translational model for silhouette motion, and generalizes polygon approximation for lossless and lossy motion estimation by adjusting a tolerance parameter d(max). To represent motion-compliant regions with minimum information in the transmitted bitstream, we develop a reference index-based coding scheme to represent the 2D positions of the matched segments using 1D reference contour indices. Finally, we encode the mismatched segments by sending residual polygons until the distortion is less than d(max). While GPSC realizes polygon approximation exactly at every encoding stage, we can guarantee quality of service because the peak distortion is no greater than d(max), and we improve coding efficiency as long as a silhouette complies with the model. The tolerance parameter d(max) can be assigned to each contour to smooth the transmitted data rate, which is especially useful for constant bandwidth channels. Compared with non-predictive approaches, simulation using MPEG-4 sequences demonstrates that GPSC not only improves objective gain but also enhances visual quality based on MPEG-4 subjective tests. The significance of GPSC is that it provides a generic framework for seamlessly extending conventional vertex coding schemes into the temporal domain yet it retains the advantages of existing polygon-based algorithms for visual content description while furnishing better geometric compression. (C) 2000 Elsevier Science B.V, All rights reserved.
In this paper, an object-oriented analysis-synthesis coder is presented the first time in its entity concentrating on an optimal relationship of its components image analysis, image synthesis and parameter coding and ...
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In this paper, an object-oriented analysis-synthesis coder is presented the first time in its entity concentrating on an optimal relationship of its components image analysis, image synthesis and parameter coding and on a comparison of its coding efficiency to block-oriented hybrid coding. As block-oriented hybrid coder, the RM8 of the CCITT is used. The presented object-oriented analysis-synthesis coder is based on the source model of moving flexible 2D-objects and encodes arbitrarily shaped objects instead of rectangular blocks. The objects are described by three parameter sets defining their motion, shape and colour (colour parameters denoting luminance as well as chrominance values of the object surface). The parameter sets of each object are obtained by image analysis and coded by an object dependent parameter coding. Using the coded parameter sets, an image can be reconstructed by model-based image synthesis. Experimental results show that transmitting shape information and allowing small position errors (geometrical distortions) avoid the mosquito and blocking artefacts of a block-oriented coder. Furthermore, important image areas such as facial areas can be reconstructed with an image quality improvement up to 4 dB using the image analysis. As a whole, the reconstructed image of an object-oriented analysis-synthesis coder appears sharper compared to block-oriented hybrid coding.
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