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Progressive Image Denoising

delete2014-07-01
delete103
PRE
AI
C
Claude Knaus *
M
Matthias Zwicker
DOI:10.1109/TIP.2014.2326771delete
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Abstract

Abstract

En 中文
Image denoising continues to be an active research topic. Although state-of-the-art denoising methods are numerically impressive and approch theoretical limits, they suffer from visible artifacts. While they produce acceptable results for natural images, human eyes are less forgiving when viewing synthetic images. At the same time, current methods are becoming more complex, making analysis, and implementation difficult. We propose image denoising as a simple physical process, which progressively reduces noise by deterministic annealing. The results of our implementation are numerically and visually excellent. We further demonstrate that our method is particularly suited for synthetic images. Finally, we offer a new perspective on image denoising using robust estimators.
Keywords:
Image denoising
robust estimation
deterministic annealing
bilateral filtering
short-time Fourier transform
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Journal

IEEE Transactions on Image Processing cover
IEEE Transactions on Image Processing
IF:
13.7
Papers:
1.0W
Citations:
8.4W

Organization

U
University of Bern
Scholars:
3.9W
Papers: 3.1W
Citations: 4.8W