Region-based change detection of PolSAR images using analytic information-theoretic divergence

In this paper a region-based change detection approach for multi-temporal PolSAR images is proposed. The PolSAR images are first segmented into compact local regions in the same way, then Wishart mixture models are learned to model each local region. To generate difference (DC) map, statistical distribution differences measured by information theoretic divergence are calculated for corresponding local region pairs. We adopt the Cauchy-Schwarz (CS) divergence as its analytic expression can be derived for Wishart mixture models. We test the proposed scheme on ALOS PALSAR PolSAR images. Qualitative and quantitative evaluations show its promising performance, compared to the traditional pixel-level approach.

[1]  Knut Conradsen,et al.  A test statistic in the complex Wishart distribution and its application to change detection in polarimetric SAR data , 2003, IEEE Trans. Geosci. Remote. Sens..

[2]  Frank Nielsen,et al.  Closed-form information-theoretic divergences for statistical mixtures , 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

[3]  A. Doulgeris,et al.  A RELAXED WISHART MODEL FOR POLARIMETRIC SAR DATA , 2009 .

[4]  Frank Nielsen,et al.  K-MLE: A fast algorithm for learning statistical mixture models , 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[5]  Pascal Fua,et al.  SLIC Superpixels Compared to State-of-the-Art Superpixel Methods , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Josef Kittler,et al.  Minimum error thresholding , 1986, Pattern Recognit..

[7]  Olga Veksler,et al.  Fast Approximate Energy Minimization via Graph Cuts , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Xiaojing Huang,et al.  Change Detection in High-Resolution SAR Images Based on Jensen–Shannon Divergence and Hierarchical Markov Model , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[9]  E. Pottier,et al.  Polarimetric Radar Imaging: From Basics to Applications , 2009 .

[10]  Frank Nielsen,et al.  Statistical exponential families: A digest with flash cards , 2009, ArXiv.

[11]  Jordi Inglada,et al.  A New Statistical Similarity Measure for Change Detection in Multitemporal SAR Images and Its Extension to Multiscale Change Analysis , 2007, IEEE Transactions on Geoscience and Remote Sensing.