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Conference Papers Year : 2006

General Adaptive Neighborhood Image Restoration, Enhancement and Segmentation

Abstract

This paper aims to outline the General Adaptive Neighborhood Image Processing (GANIP) approach [1–3], which has been recently introduced. An intensity image is represented with a set of local neighborhoods defined for each point of the image to be studied. These so-called General Adaptive Neighborhoods (GANs) are simultaneously adaptive with the spatial structures, the analyzing scales and the physical settings of the image to be addressed and/or the human visual system. After a brief theoretical introductory survey, the GANIP approach will be successfully applied on real application examples in image restoration, enhancement and segmentation.
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Dates and versions

hal-00128111 , version 1 (30-01-2007)

Identifiers

  • HAL Id : hal-00128111 , version 1

Cite

Johan Debayle, Yann Gavet, Jean-Charles Pinoli. General Adaptive Neighborhood Image Restoration, Enhancement and Segmentation. Image Analysis and Recognition, 2006, France. pp.29-40. ⟨hal-00128111⟩
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