NDLI: Recursivity and PDEs in image processing

Content Provider	IEEE Xplore Digital Library
Author	Alvarez, L. Deriche, R. Santana, F.
Copyright Year	2000
Description	Author affiliation: Dept. de Inf. y Sistemas, Univ. de Las Palmas, Spain (Alvarez, L.)
Abstract	Recursive filtering structures reduce drastically the computational effort required for different tasks in image processing. These operations are done with a fixed number of operations per output point independently of the size of the neighbourhood considered. In this paper we show that implicit numerical implementations of some partial differential equations (PDEs) provide algorithms that can be interpreted in terms of recursive filters. We show, in particular, that the classical second order recursive filter introduced by Deriche (1987, 1990) is in fact a particular implementation of the heat equation. Using the well-known Neumann boundary condition for the heat equation, we propose some new implementation of the filter. We extend this linear filter to a nonlinear recursive smoothing filter, following the general idea of anisotropic diffusion. We present some comparison results with the classical Perona-Malik model.
Starting Page	242
Ending Page	248
File Size	933958
Page Count	7
File Format	PDF
ISBN	0769507506
ISSN	10514651
DOI	10.1109/ICPR.2000.905312
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-09-03
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image processing Nonlinear filters Nonlinear equations Computer vision Filtering Convolution Smoothing methods Kernel World Wide Web Robots
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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