Perona, Pietro and Shiota, Takahiro and Malik, Jitendra (1994) Anisotropic Diffusion. In: Geometry-Driven Diffusion in Computer Vision. Computational Imaging and Vision. No.1. Springer Netherlands , Dordrecht, pp. 73-92. ISBN 9789048144617. https://resolver.caltech.edu/CaltechAUTHORS:20190328-155333804
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Abstract
The importance of multi-scale descriptions of images has been recognized from the early days of computer vision e.g. Rosenfeld and Thurston [309]. A clean formalism for this problem is the idea of scale-space filtering introduced by Witkin [386] and further developed in Koenderink [187], Babaud, Duda and Witkin[24], Yuille and Poggio [396], and Hummel [163, 164] and reviewed in the earlier sections of this book.
| Item Type: | Book Section | ||||||
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| Additional Information: | © Springer Science+Business Media Dordrecht 1994. | ||||||
| Subject Keywords: | Maximum Principle; Diffusion Equation; Maximal Monotone; Causality Criterion; Brightness Gradient | ||||||
| Series Name: | Computational Imaging and Vision | ||||||
| Issue or Number: | 1 | ||||||
| Record Number: | CaltechAUTHORS:20190328-155333804 | ||||||
| Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20190328-155333804 | ||||||
| Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||
| ID Code: | 94262 | ||||||
| Collection: | CaltechAUTHORS | ||||||
| Deposited By: | George Porter | ||||||
| Deposited On: | 28 Mar 2019 23:05 | ||||||
| Last Modified: | 03 Oct 2019 21:02 |
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