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http://dx.doi.org/10.5573/IEIESPC.2014.3.1.19

Multi-Resolution Kronecker Compressive Sensing  

Canh, Thuong Nguyen (Department of Electronic and Electrical Engineering, Sungkyunkwan University)
Quoc, Khanh Dinh (Department of Electronic and Electrical Engineering, Sungkyunkwan University)
Jeon, Byeungwoo (Department of Electronic and Electrical Engineering, Sungkyunkwan University)
Publication Information
IEIE Transactions on Smart Processing and Computing / v.3, no.1, 2014 , pp. 19-27 More about this Journal
Abstract
Compressive sensing is an emerging sampling technique which enables sampling a signal at a much lower rate than the Nyquist rate. In this paper, we propose a novel framework based on Kronecker compressive sensing that provides multi-resolution image reconstruction capability. By exploiting the relationship of the sensing matrices between low and high resolution images, the proposed method can reconstruct both high and low resolution images from a single measurement vector. Furthermore, post-processing using BM3D improves its recovery performance. The experimental results showed that the proposed scheme provides significant gains over the conventional framework with respect to the objective and subjective qualities.
Keywords
Compressive imaging; multi-resolution; Total variation; Reconstruction; Split Bregman;
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