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Spatially Adaptive Color Image Processing

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Advances in Low-Level Color Image Processing

Part of the book series: Lecture Notes in Computational Vision and Biomechanics ((LNCVB,volume 11))

Abstract

This chapter is focused on spatially adaptive image processing for color images in the context of the General Adaptive Neighborhood Image Processing (GANIP) approach. The GANIP was first defined for gray-tone images and is here extended to color images. A set of local adaptive neighborhoods is defined for each image point, depending on the color intensity function of the image. These adaptive neighborhoods are then used as spatially adaptive operational windows for defining adaptive Choquet filters and adaptive morphological filters. The resulting adaptive operators are successfully applied and compared with the classical operators for image restoration, enhancement and segmentation of color images.

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Authors and Affiliations

  1. Ecole Nationale Supérieure des Mines, LGF UMR CNRS 5307, 158 cours Fauriel, 42023 , Saint-Etienne, France

    Johan Debayle & Jean-Charles Pinoli

Authors
  1. Johan Debayle
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  2. Jean-Charles Pinoli
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Correspondence to Johan Debayle .

Editor information

Editors and Affiliations

  1. Computer Science dept., Louisiana State University, Shreveport, Louisiana, USA

    M. Emre Celebi

  2. Automatic Control, Silesian University of Technology, Gliwice, Poland

    Bogdan Smolka

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Debayle, J., Pinoli, JC. (2014). Spatially Adaptive Color Image Processing. In: Celebi, M., Smolka, B. (eds) Advances in Low-Level Color Image Processing. Lecture Notes in Computational Vision and Biomechanics, vol 11. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7584-8_6

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  • DOI: https://doi.org/10.1007/978-94-007-7584-8_6

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-7583-1

  • Online ISBN: 978-94-007-7584-8

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