吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (4): 1239-1245.doi: 10.13229/j.cnki.jdxbgxb201604033

• Orginal Article • Previous Articles     Next Articles

Supper-resolution reconstruction of infrared images of compressive coded aperture

WANG Xin-hua1, 2, OUYANG Ji-hong1, PANG Wu-bin2   

  1. 1.College of Computer Science and Technology, Jilin University, Changchun 130012, China;
    2. State Key Laboratory of Applied Optics,Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
  • Received:2015-03-05 Online:2016-07-20 Published:2016-07-20

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Abstract: In order to obtain high quality image information using infrared detector with low resolution, a compressive coded aperture imaging method based on the frequency spectrum plane and the Supper Resolution Image Reconstruction (SRIR) algorithm was investigated. First, the aperture encoder was added to the frequency spectrum plane, and the image sampling signal was compressive coded by Fourier transform. The, by virtue of the piecewise smooth of the optimal imaging system, the signal sparse representation was realized based on Fourier transform domain. Finally, the SRIR of the sparse signal was completed by improved Gradient Projection for Sparse Reconstruction (GPSR) parallel acceleration algorithm, which combined with GPSR-BB algorithm and adaptive non-monotone line search strategy. Experimental results indicate that the high resolution images can be constructed with information far less than that of the original signal.

Key words: computer application, compressed sensing, coded aperture, super resolution image reconstruction (SRIR)

CLC Number: 

  • TP394.1
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