Block Compressed Sensing Based On Image Complexity

被引:0
|
作者
Cao, Yuming [1 ]
Feng, Yan [1 ]
Jia, Yingbiao [1 ]
Dou, Changsheng [1 ]
机构
[1] Northwestern Polytech Univ, Sch Elect & Informat, Xian 710072, Peoples R China
关键词
Compressed sensing; Image Complexity; Total-Variation(TV); SPARSITY;
D O I
10.4028/www.scientific.net/AMM.157-158.1287
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Compressed sensing (CS) is a new Compressed sensing (CS) is a new technique for simultaneous data sampling and compression. Inspired by recent theoretical advances in compressive sensing, we propose a new CS algorithm which takes the image complexity into consideration. Image will be divided into small blocks, and then acquisition is conducted in a block-by-block manner. Each block has independent measurement and recovery process. The extraordinary thought proposed is that we sufficiently take advantage of image characteristics in measurement process, which make our measurement more effective and efficient. Experimental results tell that our algorithm has better recovery performance than traditional method, and its calculation amount has greatly reduced.
引用
收藏
页码:1287 / 1292
页数:6
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