Abstract
We propose a technique for detecting significant changes in a scene automatically, based on images acquired at different times. Compared to conventional luminance difference methods, the proposed technique does not require an arbitrarily-determined threshold for deciding how much change in pixel values amounts to a significant change in the scene. The technique can be used to detect the changes that occured in the scene, even when the images are of different spectral domains.
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Chua, J.J., Tischer, P.E. (2004). Automatic Change Detection Based on Codelength Differences in Multi-temporal and Multi-spectral Images. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds) Artificial Intelligence and Soft Computing - ICAISC 2004. ICAISC 2004. Lecture Notes in Computer Science(), vol 3070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24844-6_106
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DOI: https://doi.org/10.1007/978-3-540-24844-6_106
Publisher Name: Springer, Berlin, Heidelberg
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