Robust anisotropic diffusion and sharpening of scalar and vector images
1997
Conference Paper
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Relations between anisotropic diffusion and robust statistics are described. We show that anisotropic diffusion can be seen as a robust estimation procedure that estimates a piecewise smooth image from a noisy input image. The "edge-stopping" function in the anisotropic diffusion equation is closely related to the error norm and influence function in the robust estimation framework. This connection leads to a new "edge-stopping" function based on Tukey's biweight robust estimator, that preserves sharper boundaries than previous formulations and improves the automatic stopping of the diffusion. The robust statistical interpretation also provides a means for detecting the boundaries (edges) between the piecewise smooth regions in the image. We extend the framework to vector-valued images and show applications to robust image sharpening.
Author(s): | Black, M. J. and Sapiro, G. and Marimont, D. and Heeger, D. |
Book Title: | Int. Conf. on Image Processing, ICIP |
Volume: | 1 |
Pages: | 263-266 |
Year: | 1997 |
Month: | October |
Series: | Vol. 1 |
Department(s): | Perceiving Systems |
Bibtex Type: | Conference Paper (inproceedings) |
Paper Type: | Conference |
Address: | Santa Barbara, CA |
Links: |
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publisher site |
BibTex @inproceedings{Black:ICIP:1997, title = {Robust anisotropic diffusion and sharpening of scalar and vector images}, author = {Black, M. J. and Sapiro, G. and Marimont, D. and Heeger, D.}, booktitle = {Int. Conf. on Image Processing, ICIP}, volume = {1}, pages = {263-266}, series = {Vol. 1}, address = {Santa Barbara, CA}, month = oct, year = {1997}, doi = {}, month_numeric = {10} } |