Color texture analysis using CFA chromatic co-occurrence matrices

Abstract : Most color cameras are fitted with a single sensor that provides color filter array (CFA) images, in which each pixel is characterized by one of the three color components (either red, green, or blue). To produce a color image, the two missing color components have to be estimated at each pixel of the corresponding CFA image. This process is commonly referred to as demosaicing, and its result as the demosaiced color image. Since demosaicing methods intend to produce "perceptually satisfying" demosaiced color images, they attempt to avoid color artifacts. Because this is often achieved by filtering, demosaicing schemes tend to alter the local texture information that is, however, useful to discriminate texture images. To avoid this issue while exploiting color information for texture classification, it may be relevant to compute texture descriptors directly from CFA images. From chromatic co-occurrence matrices (CCMs) that capture the spatial interaction between color components, we derive new descriptors (CFA CCMs) for CFA texture images. Color textures are then compared by means of the similarity between their CFA CCMs. Experimental results achieved on benchmark color texture databases show the efficiency of this approach for texture classification.
Type de document :
Article dans une revue
Computer Vision and Image Understanding, Elsevier, 2013, 117 (7), pp.747-763. 〈10.1016/j.cviu.2013.03.001〉
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-00799371
Contributeur : Ludovic Macaire <>
Soumis le : mardi 12 mars 2013 - 10:47:50
Dernière modification le : jeudi 13 avril 2017 - 11:26:34

Identifiants

Citation

Olivier Losson, Alice Porebski, Nicolas Vandenbroucke, Ludovic Macaire. Color texture analysis using CFA chromatic co-occurrence matrices. Computer Vision and Image Understanding, Elsevier, 2013, 117 (7), pp.747-763. 〈10.1016/j.cviu.2013.03.001〉. 〈hal-00799371〉

Partager

Métriques

Consultations de la notice

263