Image and Signal Processing Methods

Block compressed sensing reconstruction with adaptive-thresholding projected Landweber for aerial imagery

[+] Author Affiliations
Hao Liu, Wensheng Wang

Donghua University, College of Information Science and Technology, 2999 North Renmin Road, Shanghai 201620, China

J. Appl. Remote Sens. 9(1), 095037 (Dec 21, 2015). doi:10.1117/1.JRS.9.095037
History: Received July 21, 2015; Accepted November 20, 2015
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Abstract.  A block compressed sensing with projected Landweber (BCS-PL) framework that incorporates the universal measurement and projected-Landweber iterative reconstruction is summarized. Based on the BCS-PL framework, an improved reconstruction algorithm for aerial imagery: block compressed sensing with adaptive-thresholding projected Landweber (BCS-ATPL), which leverages a piecewise-linear thresholding model for wavelet-based image denoising, is presented. Through analyzing the functional relation between the thresholding factors and sampling subrates, the proposed adaptive-thresholding model can effectively remove wavelet-domain noise of bivariate shrinkage. For the reconstruction quality of aerial images, experimental results demonstrate that the proposed BCS-ATPL algorithm consistently outperforms several existing BCS-PL reconstruction algorithms. With the experiment-driven methodology, the BCS-ATPL algorithm can preserve better reconstruction quality at a competitive computational cost, which makes it more desirable for aerial imagery applications.

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© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Hao Liu and Wensheng Wang
"Block compressed sensing reconstruction with adaptive-thresholding projected Landweber for aerial imagery", J. Appl. Remote Sens. 9(1), 095037 (Dec 21, 2015). ; http://dx.doi.org/10.1117/1.JRS.9.095037


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