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Proceedings Paper

A novel superresolution algorithm based on standard displacements
Author(s): Xiangquan Wei; Maozu Guo; Jianming Huang; Feng Chen
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Paper Abstract

In many imaging systems, the detector array is not sufficiently dense to adequately sample the scene with the desired field of view. In order to enhance the existed image resolution, several approaches to solve this problem have been investigated previously, such as maximum a posteriori probability (MAP), projection onto convex sets(POCS) etc. Those algorithms enhance reconstruct high resolution with reduced aliasing, from a sequence of undersampled frames. But whether POCS, or MAP estimator in space domain, image pixels are rearranged by using lexicographic ordering as a large matrix in procession. These methods have to solve a large ill-condition equation group, which leads to a big burden of computation and storage, complexity of algorithm. So they are rarely used in practical application. In order to solve these problems, a novel reconstruction high resolution(HR) image algorithm based on the standard displacements of low resolution(LR) images is proposed. Moreover, a set of recursive updating algorithm models is presented. The results of simulating experiments show that the resolution, the details as well as the definition of the high resolution image given by using our method are greatly enhanced. At the same time, the running speed of our method is greatly faster than other super-resolution methods.

Paper Details

Date Published: 30 October 2009
PDF: 12 pages
Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74981Z (30 October 2009); doi: 10.1117/12.833667
Show Author Affiliations
Xiangquan Wei, Harbin Institute of Technology (China)
Aerospace System Engineering Shanghai (China)
Maozu Guo, Harbin Institute of Technology (China)
Jianming Huang, Aerospace System Engineering Shanghai (China)
Feng Chen, Aerospace System Engineering Shanghai (China)


Published in SPIE Proceedings Vol. 7498:
MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications
Faxiong Zhang; Faxiong Zhang, Editor(s)

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