JOURNAL ARTICLE

MAP Based Super-Resolution Image Reconstruction Method

Pan HeBo Yang WangXiao Xia LiuXiao Wei Han

Year: 2012 Journal:   Applied Mechanics and Materials Vol: 220-223 Pages: 2754-2757   Publisher: Trans Tech Publications

Abstract

Super-resolution image reconstruction has been one of the most active research fields in recent years. In this paper, a new super-resolution algorithm is proposed to the problem of obtaining a high-resolution image from several low- resolution images that have been sub sampled. In the image registration, the paper puts forward an improved search strategies improving registration accuracy. In the MAP algorithm, the threshold parameters of solving the optimal value, making the estimated value of the optimal high-resolution images, so that the reconstructed image is better. The results of the experiments indicate that the proposed algorithm can not only make an automatic choice of the parameter and get the high resolution reconstruction image expected, but also can preserve the edges and details of the image effectively.

Keywords:
Image (mathematics) Computer vision Artificial intelligence Resolution (logic) Computer science Image resolution Value (mathematics) Sub-pixel resolution Algorithm Image processing Digital image processing

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Topics

Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Processing Techniques and Applications
Physical Sciences →  Engineering →  Media Technology
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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