Variational unsupervised segmentation of multi-look complex polarimetric images using a Wishart observation model
Variational unsupervised segmentation of multi-look complex polarimetric images using a Wishart observation model
Ayed, Ismail Ben and Mitiche, Amar and Belhadj, Ziad
Proceedings – International Conference on Image Processing, ICIP 2006
Abstract : We address unsupervised variational segmentation of multi-look complex polarimetric images using a Wishart observation model via level sets. The methods consists of minimizing a functional containing an original data term derived from maximum likelihood Wishart approximation and a classical boundary length prior. The minimization is carried out efficiently by first order expansion of the data term and a new multiphase method which embeds a simple partition constraint directly in curve evolution. Results are shown on both synthetic and real images. Quantitative performance evaluation and comparisons with another method are also given. ©2006 IEEE.