Block Compressed Sensing Based On Image Complexity
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.
Compressed sensing Image Complexity Total-Variation(TV)
Yuming Cao Yan Feng Yingbiao Jia Changsheng Dou
School of Electronics and InformationNorthwestern Polytechnical UniversityXi’an, China School of Electronics and Information Northwestern Polytechnical University Xi’an, China
国际会议
哈尔滨
英文
254-257
2011-01-18（万方平台首次上网日期，不代表论文的发表时间）