Color Quantization For Image Processing Using Self Information

Alain Pujol 1 Liming Chen 1
1 imagine - Extraction de Caractéristiques et Identification
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : A digital picture generally contains tens of thousands of colors. Therefore, most image processing applications first need to apply a color reduction scheme before performing further sophisticated analysis operations such as segmentation. While a lot of color reduction techniques exist in the literature, they are mainly designed for image compression and are unfortunately not suited for many image processing operations (e.g. segmentation) as they tend to alter image color structure and distribution. In this paper, we propose a new color reduction scheme (SICR), using probabilities and information theory elements to balance between the information provided by the selected colors and the necessity to accurately represent the selected colors. We also advocate for the use of perceptually accurate metrics for evaluation.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01502228
Contributor : Équipe Gestionnaire Des Publications Si Liris <>
Submitted on : Wednesday, April 5, 2017 - 11:31:07 AM
Last modification on : Wednesday, November 20, 2019 - 3:00:53 AM

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  • HAL Id : hal-01502228, version 1

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Alain Pujol, Liming Chen. Color Quantization For Image Processing Using Self Information. international Conference on Information Communications and Signal Processing (ICICS), Dec 2007, Singapore, Singapore. pp.1-5. ⟨hal-01502228⟩

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