21 December 2015 Block compressed sensing reconstruction with adaptive-thresholding projected Landweber for aerial imagery
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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.
© 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)
Hao Liu, Hao Liu, Wensheng Wang, Wensheng Wang, } "Block compressed sensing reconstruction with adaptive-thresholding projected Landweber for aerial imagery," Journal of Applied Remote Sensing 9(1), 095037 (21 December 2015). https://doi.org/10.1117/1.JRS.9.095037 . Submission:
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