Cluster Computing

, Volume 22, Supplement 4, pp 8407–8413 | Cite as

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

  • Bing Xu
  • Xiaoping Zhang
  • Xianjun WuEmail author


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.


Compressed sensing Super-resolution Sub-pixel shift 



This work is supported by Special Funds of Applied Science & Technology Research and Development of Guangdong Province, China (Grant: 2015B010128015).


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Computer and Electronic InformationGuangdong University of Petrochemical TechnologyMaomingChina
  2. 2.School of Mathematics and StatisticsThe University of SheffieldSheffieldUK
  3. 3.School of Computing CenterGuangdong University of Petrochemical TechnologyMaomingChina

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