Super-resolution image reconstruction algorithm based on sub-pixel shift

This paper studies the problem of multi-frame image super-resolution reconstruction. The process of image degradation is modeled by using the first-order Taylor expansion based on sub-pixel. Then the energy minimization function is established and the graph-cut algorithm is chosen to solve the energy minimization. In order to confirm this algorithm, we obtain the low resolution images by two ways: simulating image degradation and taking photos. By comparing the 4 × 4 times reconstruction results, it is shown that this algorithm is valid not only for simulation of low resolution images but also for real images. Besides, experimental results show that this algorithm possesses good anti-interference ability of noise.

[1]  Shree K. Nayar,et al.  Video super-resolution using controlled subpixel detector shifts , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  P. Anandan,et al.  Hierarchical Model-Based Motion Estimation , 1992, ECCV.

[3]  Olga Veksler,et al.  Fast Approximate Energy Minimization via Graph Cuts , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Hui Ji,et al.  Robust wavelet-based super-resolution reconstruction: theory and algorithm. , 2009, IEEE transactions on pattern analysis and machine intelligence.

[5]  Michal Irani,et al.  Super-resolution from a single image , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[6]  An Yao.  An Adaptive-regularized Image Super-resolution , 2012 .

[7]  Vladimir Kolmogorov,et al.  An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision , 2004, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Takeo Kanade,et al.  Limits on Super-Resolution and How to Break Them , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Nikolas P. Galatsanos,et al.  Super-Resolution Based on Fast Registration and Maximum a Posteriori Reconstruction , 2007, IEEE Transactions on Image Processing.

[10]  Zhouchen Lin,et al.  Penrose Pixels for Super-Resolution , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Liu Ju.  Super-Resolution Image Restoration Considering Sub-pixel Registration Error , 2007 .

[12]  Lian Qiu,et al.  Single Image Super-resolution Algorithm Based on Two-stage and Multi-frequency-band Dictionaries , 2013 .

[13]  Michael Elad,et al.  Fast and robust multiframe super resolution , 2004, IEEE Transactions on Image Processing.

[14]  Michael Elad,et al.  Super-Resolution Without Explicit Subpixel Motion Estimation , 2009, IEEE Transactions on Image Processing.

[15]  Gunamani Jena,et al.  POCS Based Super-Resolution Image Reconstruction Using an Adaptive Regularization Parameter , 2011, ArXiv.