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.
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© 1997 Springer-Verlag Berlin Heidelberg
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Pujas, P., Aldon, MJ. (1997). Estimation of the color image gradient with perceptual attributes. In: Del Bimbo, A. (eds) Image Analysis and Processing. ICIAP 1997. Lecture Notes in Computer Science, vol 1310. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63507-6_190
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DOI: https://doi.org/10.1007/3-540-63507-6_190
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