A variational image restoration with spatially varying noise

Zheng Bao; Hua Bai; Ruihua Liu; Chaomin Shen

doi:10.1117/12.813241

7 November 2008 A variational image restoration with spatially varying noise

Zheng Bao, Hua Bai, Ruihua Liu, Chaomin Shen

Proceedings Volume 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images; 714714 (2008) https://doi.org/10.1117/12.813241
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China

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.

Citation Download Citation

Zheng Bao, Hua Bai, Ruihua Liu, and Chaomin Shen "A variational image restoration with spatially varying noise", Proc. SPIE 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images, 714714 (7 November 2008); https://doi.org/10.1117/12.813241

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