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Phase regularisation for single image super-resolution reconstruction

Phase regularisation for single image super-resolution reconstruction

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  • Author(s): G. Cheng 1 ; J. Huang 1 ; Z. Liu 1 ; L. Cheng 2
    • View affiliations
    • Affiliations: 1: Key Laboratory of C4ISR, College of Information System and Management, National University of Defense Technology, Changsha, People's Republic of China
      2: College of Science, National University of Defense Technology, Changsha, People's Republic of China
  • Source: Volume 46, Issue 14, 8 July 2010, p. 1000 – 1001
    DOI:  10.1049/el.2010.0325 , Print ISSN 0013-5194, Online ISSN 1350-911X
© The Institution of Engineering and Technology
Published

A novel single image super-resolution reconstruction algorithm is proposed. Based on the geometrical model on the phases of complex wavelet coefficients of the image, a new image prior model leads to a powerful regularisation strategy for image super-resolution reconstruction, which is applicable to general image structures. Experimental results show that the method is effective at preserving the visual detailed information.

Inspec keywords: image reconstruction; image resolution

Other keywords: single image super-resolution reconstruction algorithm; phase regularisation; complex wavelet coefficient; geometrical model

Subjects: Optical, image and video signal processing; Computer vision and image processing techniques

References

    1. 1)
      • Sun, J., Xu, Z., Shum, H.: `Image super-resolution using gradient profile prior', IEEE Conf. CVPR, Anchorage, June 2008, USA, p. 1–8.
    2. 2)
      • M. Irani , S. Peleg . Motion analysis for image enhancement: resolution, occlusion and transparency. J. Vis. Commun. Image Represent. , 4 , 324 - 335
    3. 3)
    4. 4)
      • M. Miller , N. Kingsbury . Image modeling using interscale phase properties of complex wavelet coefficients. IEEE Trans. Image Process. , 9 , 1491 - 1499
    5. 5)
    6. 6)
      • T. Goldstein , S. Osher . The split Bregman method for L1 regularized problems. SIAM J. Imaging Sci. , 2 , 323 - 343
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