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Proceedings Paper

Image super-resolution based on image adaptive decomposition
Author(s): Qiwei Xie; Haiyan Wang; Lijun Shen; Xi Chen; Hua Han
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Paper Abstract

In this paper we propose an image super-resolution algorithm based on Gaussian Mixture Model (GMM) and a new adaptive image decomposition algorithm. The new image decomposition algorithm uses local extreme of image to extract the cartoon and oscillating part of image. In this paper, we first decompose an image into oscillating and piecewise smooth (cartoon) parts, then enlarge the cartoon part with interpolation. Because GMM accurately characterizes the oscillating part, we specify it as the prior distribution and then formulate the image super-resolution problem as a constrained optimization problem to acquire the enlarged texture part and finally we obtain a fine result.

Paper Details

Date Published: 5 December 2011
PDF: 8 pages
Proc. SPIE 8005, MIPPR 2011: Parallel Processing of Images and Optimization and Medical Imaging Processing, 80050N (5 December 2011); doi: 10.1117/12.911893
Show Author Affiliations
Qiwei Xie, Jiangsu Province Institute of Quality and Safety Engineering (China)
Institute of Automation (China)
Haiyan Wang, Jiangsu Province Institute of Quality and Safety Engineering (China)
Lijun Shen, Institute of Automation (China)
Xi Chen, Institute of Automation (China)
Hua Han, Institute of Automation (China)


Published in SPIE Proceedings Vol. 8005:
MIPPR 2011: Parallel Processing of Images and Optimization and Medical Imaging Processing
Faxiong Zhang; Faxiong Zhang, Editor(s)

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