Acta Metrologica Sinica  2017, Vol. 38 Issue (1): 69-72    DOI: 10.3969/j.issn.1000-1158.2017.01.15
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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.
Key wordsmetrology      image reconstruction      hybrid sampling      compressed sensing      interested area      compression ratio     
Received: 28 January 2015      Published: 28 December 2016
PACS:  TB96  
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ZHANG Shu-qing
HU Yong-tao
WANG Shi-hao
JI Bing-shuo
JIANG Wan-lu
Cite this article:   
ZHANG Shu-qing,HU Yong-tao,WANG Shi-hao, et al. Compressed Sensing Reconstruction Algorithm Based on Hybrid Sampling[J]. Acta Metrologica Sinica, 2017, 38(1): 69-72.
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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2017.01.15     OR     http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2017/V38/I1/69
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