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Proceedings Paper

Facet-based adaptive anisotropic diffusion for image selective smoothing
Author(s): Guodong Wang; Nong Sang; Luxin Yan; Xubang Shen
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Paper Abstract

In each step of anisotropic diffusion smoothing, noises must be managed to get better results. The mostly used method is Gaussian filtering. However, the standard deviation of the Gaussian filter can't be accurately obtained and it should change during the iterative process. Another problem is how to select a proper standard deviation to reducing noises while preserving edges. Actually, facet model fitting can be taken as a natural way to overcome the drawbacks mentioned above. Facet model fitting has the low-pass filtering performance adaptive to the image during evolution of diffusion; it can also achieve balanced results for noise reduction and edge preserving. Experiments show the method can preserve more edges as well as obtain higher peak signal-to-noise ratio as compared to other anisotropic diffusion based selective smoothing approaches.

Paper Details

Date Published: 15 November 2007
PDF: 9 pages
Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67861E (15 November 2007); doi: 10.1117/12.748279
Show Author Affiliations
Guodong Wang, Huazhong Univ. of Science and Technology (China)
Nong Sang, Huazhong Univ. of Science and Technology (China)
Luxin Yan, Huazhong Univ. of Science and Technology (China)
Xubang Shen, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 6786:
MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition

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