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Proceedings Paper

A variational image restoration with spatially varying noise
Author(s): Zheng Bao; Hua Bai; Ruihua Liu; Chaomin Shen
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Paper Abstract

The noise in natural images sometimes changes according to imaging mechanism or local image information. This is called spatially varying noise. It is obvious that classical variational denoising algorithms such as the Rudin-Osher-Fatemi model are not suitable for this kind of noise. We propose a variational method to remove this spatially varying noise based on the estimation of local variance for a given image, such that high noise regions are smoothed meanwhile the textures and certain details in low noise regions are preserved. Moreover, we give the proof of existence of the minimizer of our proposed functional. The experimental results show visual improvement and high signal-to-noise ratio over other variational denoising models.

Paper Details

Date Published: 7 November 2008
PDF: 8 pages
Proc. SPIE 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images, 714714 (7 November 2008); doi: 10.1117/12.813241
Show Author Affiliations
Zheng Bao, East China Normal Univ. (China)
Hua Bai, Shanghai Remote Sensing and Applied Measurement Ctr. (China)
Ruihua Liu, Chongqing Institute of Technology (China)
Chaomin Shen, East China Normal Univ. (China)


Published in SPIE Proceedings Vol. 7147:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images
Lin Liu; Xia Li; Kai Liu; Xinchang Zhang, Editor(s)

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