POCS Super-Resolution Sequence Image Reconstruction Based on Image Registration Excluded Aliased Frequency Domain

This paper introduces the theory of super-resolution image reconstruction and degraded model in brief, and presents a new super-resolution image reconstruction algorithm .The algorithm bases on the new image registration excluded aliased frequency domain and the Projection Onto Convex Set (POCS) method. The algorithm can precisely estimate the image registration parameter by excluding aliased frequency domain of the low-resolution images and killing the center part of the magnitude spectrum. In order to compute the shifts and the rotation angle, we set up the polar coordinates in the center of the image. By computing the frequency function of the rotation angle by integrating over radial lines, the algorithm converts the two-dimension correlation to one-dimension correlation. And then, the POCS method is used to reconstruct high-resolution image from these aliased image sequences. As a result, we find that the reconstruction algorithm has the same precision of image registration as the spatial image registration and good effect of super-resolution image reconstruction.

Authors and Affiliations

1. Department of Surveying and Land Information Engineering, Central South University, Changsha, Hunan, 410083, China

   Chong Fan & Jianjun Zhu

2. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, Hubei, 430079, China

   Chong Fan, Jianya Gong & Lihua Zhang

3. Dept. of Hydrography and Cartography, Dalian Naval Academy, 667, Jiefang Road, Dalian, Liaoning, 116018, China

   Lihua Zhang

Editors and Affiliations

1. Institute of Intelligent Machines , Chinese Academy of Sciences , Anhui, Hefei, China

   De-Shuang Huang

2. Queen’s University , Belfast, UK

   Kang Li  & George William Irwin  & 

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© 2006 Springer-Verlag Berlin Heidelberg

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