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Motifs locaux binaires pour la classification d'images de textures multispectrales

Abstract : To discriminate gray-level texture images, spatial texture descriptors can be extracted using the local binary pattern (LBP) operator. In this paper we design an LBP operator that jointly extracts the spatial and spectral texture information directly from a raw image provided by a camera equipped with a multispectral filter array. Extensive experiments on a large dataset show that the proposed descriptor has both low computation cost and high discriminative power with regard to classical LBP descriptors applied to multispectral images.
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Submitted on : Thursday, February 20, 2020 - 2:53:47 PM
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  • HAL Id : hal-02436371, version 1


Sofiane Mihoubi, Olivier Losson, Benjamin Mathon, Ludovic Macaire. Motifs locaux binaires pour la classification d'images de textures multispectrales. XXVIIème Colloque francophone de traitement du signal et des images, GRETSI 2019, Aug 2019, Lille, France. ⟨hal-02436371⟩



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