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ICIP
2006
IEEE

Variational Unsupervised Segmentation of Multi-Look Complex Polarimetric Images using a Wishart Observation Model

14 years 8 months ago
Variational Unsupervised Segmentation of Multi-Look Complex Polarimetric Images using a Wishart Observation Model
We address unsupervised variational segmentation ofmulti-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.
Ismail Ben Ayed, Amar Mitiche, Ziad Belhadj
Added 22 Oct 2009
Updated 14 Nov 2009
Type Conference
Year 2006
Where ICIP
Authors Ismail Ben Ayed, Amar Mitiche, Ziad Belhadj
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