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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
computer science
An a-contrario approach for subpixel change detection in satellite imagery
IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 32, No. 11, Article 5406527, Year 2010
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Description
This paper presents a new method for unsupervised subpixel change detection using image series. The method is based on the definition of a probabilistic criterion capable of assessing the level of coherence of an image series relative to a reference classification with a finer resolution. In opposition to approaches based on an a priori model of the data, the model developed here is based on the rejection of a nonstructured modelcalled a-contrario modelby the observation of structured data. This coherence measure is the core of a stochastic algorithm which automatically selects the image subdomain representing the most likely changes. A theoretical analysis of this model is led to predict its performances, in particular regarding the contrast level of the image as well as the number of change pixels in the image. Numerical simulations are also presented that confirm the high robustness of the method and its capacity to detect changes impacting more than 25 percent of a considered pixel under average conditions. An application to land-cover change detection is then provided using time series of satellite images. © 2006 IEEE.
Authors & Co-Authors
Robin, Amandine
South Africa, Johannesburg
University of the Witwatersrand
Moisan, Lionel
France, Paris
Université Paris Cité
Le Hegarat-Mascle, Sylvie
France, Gif-sur-yvette
Université Paris-saclay
Statistics
Citations: 103
Authors: 3
Affiliations: 3
Identifiers
Doi:
10.1109/TPAMI.2010.37
ISSN:
01628828