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Estimation of the color image gradient with perceptual attributes

  • Philippe Pujas
  • Marie-José Aldon
Poster Session A: Color & Texture, Enhancement, Image Analysis & Pattern Recognition, Segmentation
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1310)

Abstract

Classical gradient operators are generally defined for grey level images and are very useful for image processing such as edge detection, image segmentation, data compression and object extraction. Some attempts have been made to extend these techniques to multi-component images. However, most of these solutions do not provide an optimal edge enhancement.

In this paper we propose a general formulation of the gradient of a multi-image. We first give the definition of the gradient operator, and then we extend it to multi-spectral images by using a metric and a tensorial formula. This definition is applied to the case of RGB images. Then we propose a perceptual color representation and we show that the gradient estimation may be improved by using this color representation space. Different examples are provided to illustrate the efficiency of the method and its robustness for color image analysis.

Keywords

Color Image Gradient Magnitude Perceptual Space Gradient Estimator Sobel Operator 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Philippe Pujas
    • 1
  • Marie-José Aldon
    • 2
  1. 1.Institut Universitaire de Technologie de MontpellierUniversité Montpellier IIBéziersFrance
  2. 2.LIRMM - UMR C55060 - CNRS/Université Montpellier IIMontpellier Cedex 05France

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