Noise synthetic aperture radar (SAR) imagery compressing and reconstruction based on compressed sensing

Huihuang Zhao; Juan F. Lopez Jr.; Shuxia Li; Yufeng Cao; Zhijun Qiao

doi:10.1117/12.2019120

29 May 2013 Noise synthetic aperture radar (SAR) imagery compressing and reconstruction based on compressed sensing

Huihuang Zhao, Juan F. Lopez Jr., Shuxia Li, Yufeng Cao, Zhijun Qiao

Proceedings Volume 8750, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI; 87500N (2013) https://doi.org/10.1117/12.2019120
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

Abstract

In this paper, a denoise approach is proposed to reduce the speckle noise in SAR images based on compress sensing. Through the skill of compressed sensing, we divide the image into some blocks, and propose an image reconstruction method based on block compressing sensing with Orthogonal Matching Pursuit. By adding some simulated speckle noise in the SAR image, the performance of the proposed approach is shown and compared with a conventional algorithm. the result has been shown that our method can get better result in terms of peak signal noise ratio (PSNR).

Citation Download Citation

Huihuang Zhao, Juan F. Lopez Jr., Shuxia Li, Yufeng Cao, and Zhijun Qiao "Noise synthetic aperture radar (SAR) imagery compressing and reconstruction based on compressed sensing", Proc. SPIE 8750, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI, 87500N (29 May 2013); https://doi.org/10.1117/12.2019120

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