Color Image Edge Detection by Robust Anisotropic Diffusion

Harold I. A. Bustos, Hae Yong Kim.

DOI: 10.14209/its.2002.515

Evento: 2002 International Telecommunications Symposium (ITS2002)

Keywords:

Abstract

"Edge detection is an important operation in many image-processing applications. Anisotropic diffusion is one of most reliable edge detection methods. There are many anisotropic diffusion techniques for grayscale images. However, there are only few works on the diffusion for color images, and these all use the traditional diffusion function defined by MalikPerona. Recently, \u201crobust anisotropic diffusion\u201d was proposed for grayscale images. This method is based on Tukey\u2019s robust estimator, and it converges much faster than traditional Malik-Perona\u2019s diffusion. Consequently, the new technique better preserves edges and attenuates undesirable noises. So, the edge detection becomes even more reliable. In this paper, we propose to use the Tukey\u2019s estimator to detect edges in color images. This technique is executed through two independent diffusion processes. In the first, the complex chromaticity function is diffused. The second process diffuses the scalar intensity. The results of these two diffusions are combined to detect edges. We have compared the obtained results with the Malik-Perona\u2019s conventional technique. The new method indeed converges faster, yielding sharper edges."

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