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Fast multi-channel image reconstruction using a novel two-dimensional algorithm

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Abstract

Recently, two 2D algorithms for super resolution image reconstruction based on a matrix observation model were presented. They can greatly reduce computational cost and storage requirement but are suitable for the cases of face images or no warping operator. In this paper, for wide applications we propose a novel 2D algorithm to reconstruct a high-resolution image from multiple warped and degraded low-resolution images. The proposed 2D algorithm minimizes a new cost function with two regularization terms where one is the Laplacian regularization term for robustness to noise and another is learning term for more high frequency information. Simulation results show that the proposed 2D algorithm can obtain better results in terms of both PSNR and visual quality than the two existing 2D algorithms.

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Acknowledgments

The authors thank the editor and reviewers for their encouragement and valued comments, which helped in improving the quality of the paper. This work is supported by the National Natural Science Foundation of China under Grant No. 61179037 and 60875085.

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Authors and Affiliations

  1. Department of Software Engineering, Fuzhou University, Fuzhou, China

    Shi Quan Bin & You Sheng Xia

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  1. Shi Quan Bin
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  2. You Sheng Xia
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Correspondence to You Sheng Xia.

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Bin, S.Q., Xia, Y.S. Fast multi-channel image reconstruction using a novel two-dimensional algorithm. Multimed Tools Appl 71, 2015–2028 (2014). https://doi.org/10.1007/s11042-013-1371-6

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  • DOI: https://doi.org/10.1007/s11042-013-1371-6

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