Change Detection in Sequences of Images by Multifractal Analysis

Abstract : In this work, we propose a multifractal approach to the problem of change detection in image sequences, such as registrated remotely sensed images of the same scene or sequences of medical images. We show that the multifractal analysis of images -- based on a modelisation of the two-dimensional signal as measure -- can be of great help if we want to detect changes without any a priori knowledge of the objects to be extracted. We first present a simple change detection method based on the classical multifractal analysis of images w.r.t. the Lebesgue measure. We then describe an improved method based on the analysis of images w.r.t. a reference measure, which in this case is the first image of the sequence. We finally show some results on real data.
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Communication dans un congrès
ICASSP'96 - IEEE International Conference On Acoustics, Speech and Signal Processing, May 1996, Atlanta, United States. IEEE Signal processing society, 4, pp.2172-2175, 1996, 〈10.1109/ICASSP.1996.545850〉
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Christophe Canus, Jacques Lévy Véhel. Change Detection in Sequences of Images by Multifractal Analysis. ICASSP'96 - IEEE International Conference On Acoustics, Speech and Signal Processing, May 1996, Atlanta, United States. IEEE Signal processing society, 4, pp.2172-2175, 1996, 〈10.1109/ICASSP.1996.545850〉. 〈inria-00593324〉

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