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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机译：提出了一种结合区域分割和几何运动估计的基于区域的视频编码新技术。应用基于直方图凹度和概率松弛的区域分割算法提取重要区域。除运动矢量之外，分割中区域的合并还取决于区域的属性。一种基于对象的几何特征和可伸缩平移不变旋转移位（STIRS）签名的新方法被应用于全局区域的运动估计。矢量量化（VQ）技术用于解决由于非刚性物体运动引起的问题。利用这些技术，可以以良好的性能和相对较低的复杂度提取关键区域。此外，提出了一种未覆盖/重叠的运动补偿方法。将积分算法与横山算法进行比较（Yokoyama et al。，1995，IEEE Trans。Circuit Systems Video Technol。5，500-507）。我们的仿真显示出在SNR改善和计算需求减少方面均具有改进的性能。例如，对于“美国小姐序列”，我们的计算时间减少了约15％，SNR改善了约0.8 dB。帧间SNR的变化也小得多，这意味着帧之间的视觉质量也非常稳定。
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