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Cluster Computing
Published in: Cluster Computing 4/2019

25-01-2018

Super-resolution compressed sensing imaging algorithm based on sub-pixel shift

Authors: Bing Xu, Xiaoping Zhang, Xianjun Wu

Published in: Cluster Computing | Special Issue 4/2019

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Abstract

At present, some digital signal processing methods have attracted more and more attention in improving the resolution of images. Sub-pixel shift has been widely applied in improving the resolution of compressed sensing imaging system. The resolution of the compressed sensing imaging system is limited by pixel size of the modulation system. To overcome the resolution limitation of compressed sensing imaging system, a sub-pixel shift method is proposed to enhance the resolution of modulation information and achieve super-resolution images by compressed sensing imaging system. The principle of the proposed method is introduced and the proposed method is verified using numerical simulations. Experimental results revealed that the proposed method can effectively improve the resolution of compressed sensing imaging system and obtain super-resolution image information. Additionally, the signal to noise ratio of restoration results is positively related to the sample size.
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Metadata
Title
Super-resolution compressed sensing imaging algorithm based on sub-pixel shift
Authors
Bing Xu
Xiaoping Zhang
Xianjun Wu
Publication date
25-01-2018
Publisher
Springer US
Published in
Cluster Computing / Issue Special Issue 4/2019
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-018-1839-2

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