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SuperResolution Image Reconstruction Using a Hybrid Bayesian Approach

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Neural Information Processing (ICONIP 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4233))

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Abstract

There are increasing demands for high-resolution (HR) images in various applications. Image superresolution (SR) reconstruction refers to methods that increase image spatial resolution by fusing information from either a sequence of temporal adjacent images or multi-source images from different sensors. In the paper we propose a hybrid Bayesian method for image reconstruction, which firstly estimates the unknown point spread function(PSF) and an approximation for the original ideal image, and then sets up the HMRF image prior model and assesses its tuning parameter using maximum likelihood estimator, finally computes the regularized solution automatically. Hybrid Bayesian estimates computed on actual satellite images and video sequence show dramatic visual and quantitative improvements in comparison with the bilinear interpolation result, the projection onto convex sets (POCS) estimate and Maximum A Posteriori (MAP) estimate.

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Author information

Authors and Affiliations

  1. Zhengzhou Institute of Surveying and Mapping, No. 66 Longhai Middle Road, Zhengzhou, 450052, China

    Tao Wang, Yan Zhang & Yong Sheng Zhang

Authors
  1. Tao Wang
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  2. Yan Zhang
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  3. Yong Sheng Zhang
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Editor information

Editors and Affiliations

  1. Dept. of Computer Science and Engineering, The Chinese Univ. of Hong Kong, Shatin, N.T., Hong Kong

    Irwin King

  2. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  3. The Chinese University of Hong Kong, Shatin, N.T., Hong Kong

    Lai-Wan Chan

  4. Department of Computer Science and Engineering & Center for Cognitive Science, The Ohio State University, OH 43210, Columbus

    DeLiang Wang

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© 2006 Springer-Verlag Berlin Heidelberg

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Wang, T., Zhang, Y., Zhang, Y.S. (2006). SuperResolution Image Reconstruction Using a Hybrid Bayesian Approach. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4233. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893257_46

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  • DOI: https://doi.org/10.1007/11893257_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46481-5

  • Online ISBN: 978-3-540-46482-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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