电子学报2018，Vol.46Issue(3)：544-553,10.DOI:10.3969/j.issn.0372-2112.2018.03.005
视频压缩感知中基于结构相似的帧间组稀疏表示重构算法研究
Research on Structural Similarity Based Inter-Frame Group Sparse Representation for Compressed Video Sensing
摘要
Abstract
Based on the nonlocal similarity and the correlation among inter-frames in video sequences, this paper proposes an algorithm of structural similarity based inter-frame group sparse representation (SSIM-InterF-GSR), which effectively improves the reconstruction performance for compressed video sensing. In SSIM-InterF-GSR, the structural similarity (SSIM)is utilized as block matching criterion to generate the group of similar blocks from the current frame and reference frames. And then, the sparsity of the groups is used as the regularization term to reconstruct the current frame. Meanwhile, the step-decreasing scheme for number of matching blocks is proposed during the iteration process of SSIM-InterF-GSR. Simulation results show that, compared to the state-of-the-art compressed video sensing reconstruction algorithm (Up-SeAWEN-HHP), the SSIM-InterF-GSR algorithm obtains a better reconstruction quality. The most gap is up to 4～5dB.关键词
非局部相似性/视频压缩感知/组稀疏表示/相似块组Key words
nonlocal similarity/compressed video sensing/group-based sparse representation/the group of similar blocks分类
信息技术与安全科学引用本文复制引用
和志杰,杨春玲,汤瑞东..视频压缩感知中基于结构相似的帧间组稀疏表示重构算法研究[J].电子学报,2018,46(3):544-553,10.基金项目
国家自然科学基金(No.61471173) （No.61471173）
广东省自然科学基金(No.2016A030313455) （No.2016A030313455）
