PATCH-BASED MARKOVMODELS FOR CHANGE DETECTION IN IMAGE SEQUENCE ANALYSIS

Abstract : Change detection between two images is challenging and needed in a wide variety of imaging applications. Several approaches have been yet developed, especially methods based on difference image. In this paper, we propose an original patch-based Markov modeling framework to detect spatial irregularities in the difference image with low false alarm rates. Experimental results show that the proposed approach performs well for change detection, especially for images with low signal-to-noise ratios.
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Communication dans un congrès
LNLA - International Workshop on Local and Non-Local Approximation in Image Processing - 2008, Aug 2008, Lausanne, Switzerland. 2008
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Thierry Pécot, Charles Kervrann. PATCH-BASED MARKOVMODELS FOR CHANGE DETECTION IN IMAGE SEQUENCE ANALYSIS. LNLA - International Workshop on Local and Non-Local Approximation in Image Processing - 2008, Aug 2008, Lausanne, Switzerland. 2008. 〈hal-00919698〉

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