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Perceptual Image Representation


This paper describes a rarity-based visual attention model working on both still images and video sequences. Applications of this kind of models are numerous and we focus on a perceptual image representation which enhances the perceptually important areas and uses lower resolution for perceptually less important regions. Our aim is to provide an approximation of human perception by visualizing its gradual discovery of the visual environment. Comparisons with classical methods for visual attention show that the proposed algorithm is well adapted to anisotropic filtering purposes. Moreover, it has a high ability to preserve perceptually important areas as defects or abnormalities from an important loss of information. High accuracy on low-contrast defects and scalable real-time video compression may be some practical applications of the proposed image representation.



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Correspondence to Matei Mancas.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Mancas, M., Gosselin, B. & Macq, B. Perceptual Image Representation. J Image Video Proc 2007, 098181 (2007).

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  • Image Processing
  • Pattern Recognition
  • Computer Vision
  • Human Perception
  • Video Sequence