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Proceedings Paper

The image super-resolution reconstruction based on wavelet decomposition and Markov random field
Author(s): Hongjiu Tao; Keming Jia; Xiaojun Tong
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Paper Abstract

Taking into account the lack of prior-information on account of single image, we design a image super-resolution reconstruction method, based on the possibility and the theory basis of the single image super-resolution reconstruction. Analysis of the process of the algorithm is also included. Because the theory and method of Markov random field are being developed constantly, the theory and method may described the part statistic of the image. The paper analyses the image super resolution reconstruction based on Markov Random Field, this apply the image super resolution processing. This presented a super resolution reconstruction technique based on wavelet decomposition and Markov Random Field, and has carried on the experimental research. Experiment result proves that the super resolution processing method on the basis of the Markov random field (MRF) can obtain the good super resolution restoration processing result.

Paper Details

Date Published: 8 February 2005
PDF: 6 pages
Proc. SPIE 5637, Electronic Imaging and Multimedia Technology IV, (8 February 2005); doi: 10.1117/12.573863
Show Author Affiliations
Hongjiu Tao, Wuhan Polytechnic Univ. (China)
Wuhan Univ. of Technology (China)
Keming Jia, Wuhan Polytechnic Univ. (China)
Wuhan Univ. of Technology (China)
Xiaojun Tong, Wuhan Polytechnic Univ. (China)
Wuhan Univ. of Technology (China)


Published in SPIE Proceedings Vol. 5637:
Electronic Imaging and Multimedia Technology IV
Chung-Sheng Li; Minerva M. Yeung, Editor(s)

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