基于模糊聚类和网格变形的自适应时-空差错掩盖方法

郭秀江; 朱秀昌

基于模糊聚类和网格变形的自适应时-空差错掩盖方法

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出版历程
- 收稿日期: 2004-12-09
- 修回日期: 2005-06-27
- 刊出日期: 2006-08-19

An Adaptive Spatio-Temporal Concealment Method Using Fuzzy Classifing and Mesh Warping

摘要

摘要: 当视频传输中出现不能恢复的误码或丢包时，在接收端就要使用差错掩盖技术对损坏的视频进行掩藏。该文提出了一种基于模糊聚类和网格变形的自适应差错掩盖方法，使得错误恢复效果提高。该方法首先用基于时-空的模糊聚类块匹配方法补偿平移运动场景中的块丢失，然后如果检测出丢失块所在的空间有旋转、缩放等复杂运动，则用基于网格变形的方法进行补偿。实验结果表明其PSNR值比Luigi(2001)的BMA-MBW方法平均提高约1.5dB，比传统的基于块匹配的方法平均提高约3.5dB。
- 图像处理;模糊集;聚类分析; 差错掩盖;网格变形
Abstract: When bit errors occur during transmission and cannot be corrected by an error correction scheme, error concealment is needed to mask damaged image at receiver. In this paper, a spatio-temporal error concealment algorithm based on fuzzy classify and mesh warping method is presented. The algorithm include two steps: First , the error blocks which are in the situation of pure translation are reconstructed. If the complicated motion such as rotation and zoom in or out is detected , the internal texture of each block is warped by a mesh-based affine transform, in order to comply with nontranslation. Experimental results show that the PSNR has been improved 1.5dB than the BMA-MBW, and 3.5dB than the BMA.

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