A Mixed Markov model for change detection in aerial photos with large time differences

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.

• Type: Conference
• Year: 2008
• Where: ICPR
• Authors: Csaba Benedek, Tamás Szirányi
• Keywords: Combines Global Intensity, Computer Vision, ICPR 2008, Multi-layer Mixed Markov, Registered Aerial Images