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| Compressed Sensing Reconstruction Algorithm Based on Hybrid Sampling |
| ZHANG Shu-qing,HU Yong-tao,WANG Shi-hao,JI Bing-shuo,JIANG Wan-lu |
| Institute of Electrical Engineering, the Key Lab of Measurement Technology and Instrumentation of Hebei Province, Yanshan University, Qinhuangdao, Hebei 066004, China |
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Abstract In order to improve the image reconstruction quality and the reconstruction time with high compression ratio, a compression perception reconstruction algorithm based on hybrid sampling is proposed. The image is divided into the interested and non-interested area. It used the orthogonal matching pursuit (OMP) algorithm with better quality of recovery for the interested area, and the Stagewise Orthogonal Matching Pursuit algorithm with the recovery time shorter for the non-interested area. In the interested image, the gray level of the parts except the interested region is set to zero, so as to increase the rate of sampling and image sparse degree. Experiments show that this method could restore the interested area of an imagine better, and maintain a high compression ratio.
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Received: 28 January 2015
Published: 28 December 2016
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2017, Vol. 38 
