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An image change detection algorithm based on Markov random field models

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2 Author(s)
Kasetkasem, T. ; Dept. of Electr. Eng. & Comput. Sci., Syracuse Univ., NY, USA ; Varshney, P.K.

This paper addresses the problem of image change detection (ICD) based on Markov random field (MRF) models. MRF has long been recognized as an accurate model to describe a variety of image characteristics. Here, we use the MRF to model both noiseless images obtained from the actual scene and change images (CIs), the sites of which indicate changes between a pair of observed images. The optimum ICD algorithm under the maximum a posteriori (MAP) criterion is developed under this model. Examples are presented for illustration and performance evaluation.

Published in:

Geoscience and Remote Sensing, IEEE Transactions on  (Volume:40 ,  Issue: 8 )