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Journal of Applied Remote Sensing

Block compressed sensing reconstruction with adaptive-thresholding projected Landweber for aerial imagery
Author(s): Hao Liu; Wensheng Wang
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Paper 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.

Paper Details

Date Published: 21 December 2015
PDF: 13 pages
J. Appl. Remote Sens. 9(1) 095037 doi: 10.1117/1.JRS.9.095037
Published in: Journal of Applied Remote Sensing Volume 9, Issue 1
Show Author Affiliations
Hao Liu, Donghua Univ. (China)
Wensheng Wang, Donghua Univ. (China)


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