Multiregion Level-Set Partitioning of Synthetic Aperture Radar Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonparametric Level-Set Segmentation Based on the Minimization of the Stochastic Complexity
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Characterization of imaging phone cameras using minimum description length principle
WSEAS Transactions on Information Science and Applications
SAR imagery segmentation by statistical region growing and hierarchical merging
Digital Signal Processing
Continuous force field analysis for generalized gradient vector flow field
Pattern Recognition
SAR image segmentation based on Kullback-Leibler distance of edgeworth
PCM'10 Proceedings of the 11th Pacific Rim conference on Advances in multimedia information processing: Part I
Smooth contour coding with minimal description length active grid segmentation techniques
Pattern Recognition Letters
Minimum description length characterization of low end color cameras
CIMMACS'07 Proceedings of the 6th WSEAS international conference on Computational intelligence, man-machine systems and cybernetics
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We present a new minimum description length (MDL) approach based on a deformable partition - a polygonal grid - for automatic segmentation of a speckled image composed of several homogeneous regions. The image segmentation thus consists in the estimation of the polygonal grid, or, more precisely, its number of regions, its number of nodes and the location of its nodes. These estimations are performed by minimizing a unique MDL criterion which takes into account the probabilistic properties of speckle fluctuations and a measure of the stochastic complexity of the polygonal grid. This approach then leads to a global MDL criterion without an undetermined parameter since no other regularization term than the stochastic complexity of the polygonal grid is necessary and noise parameters can be estimated with maximum likelihood-like approaches. The performance of this technique is illustrated on synthetic and real synthetic aperture radar images of agricultural regions and the influence of different terms of the model is analyzed.