文章基本信息

标题：A RECONSTRUCTION ALGORITHM WITH ADAPTIVE WEIGHTED FUSION IN COMPRESSED SENSING
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作者：YANJUN HU ; ZHONGYU LIU ; JIE XIANG 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2012
卷号：42
期号：1
页码：137-141
出版社：Journal of Theoretical and Applied
摘要：An efficient energy-saving method is proposed by taking the advantages of lightweight encoder and high compression efficiency of Compressed Sensing, which is extremely suitable for image nodes in Wireless Multi-media Sensor Networks. However, the Orthogonal Matching Pursuit (OMP) reconstruction algorithms in CS can not balance the reconstruction image quality and processing time. A novel reconstruction algorithm is proposed in this paper. This algorithm fuses images which reconstructed by OMP according to the row vectors column vectors and diagonal vectors of sample data. And the fusion weights are adjusted by calculating the PSNR values among RIRV (Reconstructed Image by Row Vectors), RICV (Reconstructed Image by Column Vectors) and RIDV (Reconstructed Image by Diagonal Vectors). Experiments show this algorithm is workable, and it reduces the stripe noise. Also, it has a better performance of balancing the reconstruction image quality and processing time than traditional OMP and CoSamp algorithms.
关键词：Compressed Sensing; Image Fusion; Orthogonal Matching Pursuit; Adaptive Weighted Fusion