Wavelet based statistical detection of salient points by the exploitation of the interscale redundancies

Authors:
W. Ayadi;A. Benazza-Benyahia
Affiliations:
Unité de Recherche en Imagerie Satellitaire et ses Applications, SUP'COM, Tunisia and Mathématiques Appliquées Paris 5, Université René Descartes Paris, France;Mathématiques Appliquées Paris 5, Université René Descartes Paris, France
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

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Abstract

In this paper, we develop a method to detect salient points at different scales in a given image. The principle of our approach is to consider a salient point as an outlier. Our contribution is twofold. The first novelty of our work consists of applying robust outliers statistical tests on the multiresolution representation of the underlying image. Besides, the second contribution relies on the exploitation of the interscale redundancies of the wavelet coefficients during the detection step. Experimental results carried out on real and synthetic images illustrate the performances of this new detection scheme.