Abstract

A new region-based video coding technique, which combines region segmentation and geometric motion estimation, is proposed in this paper. The region segmentation algorithm based on both the histogram concavities and the probabilistic relaxation is applied to extract the significant regions. The merging of regions in the segmentation depends on the attributes of the regions, besides the motion vectors. A new approach based on the geometric features of objects and the scalable translation invariant rotation-to-shifting (STIRS) signatures is applied to the motion estimation of the global regions. Vector quantization (VQ) techniques are employed to solve the problems due to nonrigid object motions. With these techniques, the critical regions can be extracted with good performance and relatively low complexity. Furthermore, an uncovered/overlapped motion compensation method is presented. The integral algorithm is compared to Yokoyama's algorithm (Yokoyama et al., 1995, IEEE Trans. Circuit Systems Video Technol.5, 500–507). Our simulations show improved performance, in terms of both SNR improvement and reduction of computational requirements. For example, we achieve about 15% reduction of computational time and about 0.8 dB improvement in SNR for the “Miss America sequence.” The frame-to-frame SNR variation is also much smaller, which implies that the visual quality between frames is also very stable.

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