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

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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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Acknowledgements

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

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Authors and Affiliations

  1. School of Computer and Electronic Information, Guangdong University of Petrochemical Technology, Maoming, China

    Bing Xu

  2. School of Mathematics and Statistics, The University of Sheffield, Sheffield, S3 7RH, UK

    Xiaoping Zhang

  3. School of Computing Center, Guangdong University of Petrochemical Technology, Maoming, China

    Xianjun Wu

Authors
  1. Bing Xu
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  2. Xiaoping Zhang
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  3. Xianjun Wu
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Correspondence to Xianjun Wu.

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Xu, B., Zhang, X. & Wu, X. Super-resolution compressed sensing imaging algorithm based on sub-pixel shift. Cluster Comput 22 (Suppl 4), 8407–8413 (2019). https://doi.org/10.1007/s10586-018-1839-2

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  • DOI: https://doi.org/10.1007/s10586-018-1839-2

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