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Proceedings Paper

Image quantization by nonlinear smoothing
Author(s): Luis Alvarez; Julio Esclarin
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Paper Abstract

We present a quantization technique based on the partial differential equation (∂u/∂t) = g(||∇(Gσ * u)||) |∇u|div(∇u/|∇u|) + f(u, t) where |∇u|div(∇u/|∇u|) represents the derivative of the function u in the direction orthogonal to the gradient, Gs is a linear convolution kernel, g is a decreasing function and f(s, t) is a lipschitz function. We assume that when t tends to +∞, f(s,t) tends uniformly to a function f(s) which has a finite number of zeros with negative derivative which act as attractors in the system and represent the quantization levels. The location of the zero-crossing of the function fs(s) depends on the histogram of the initial image given by u0. We introduce a new energie based in the Lloyd model to compute the quantizer levels. We develop a numerical scheme to discretize the above equation and we present some experimental results.

Paper Details

Date Published: 1 September 1995
PDF: 11 pages
Proc. SPIE 2567, Investigative and Trial Image Processing, (1 September 1995); doi: 10.1117/12.218473
Show Author Affiliations
Luis Alvarez, Univ. de Las Palmas de Gran Canaria (Spain)
Julio Esclarin, Univ. de Las Palmas de Gran Canaria (Spain)


Published in SPIE Proceedings Vol. 2567:
Investigative and Trial Image Processing
Leonid I. Rudin; Simon K. Bramble, Editor(s)

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