In the paper we propose a novel multi-layer Mixed Markov model for detecting relevant changes in registered aerial images taken with significant time differences. The introduced approach combines global intensity statistics with local correlation and contrast features. A global energy optimization process simultaneously ensures optimal local feature selection and smooth, observation-consistent classification. Validation is given on real aerial photos.
|Title of host publication||2008 19th International Conference on Pattern Recognition, ICPR 2008|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Publication status||Published - Jan 1 2008|
|Name||Proceedings - International Conference on Pattern Recognition|
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition