Multiregion level-set partitioning of synthetic aperture radar images.
The purpose of this study is to investigate Synthetic Aperture Radar (SAR) image segmentation into a given but arbitrary number of gamma homogeneous regions via active contours and level sets. The segmentation of SAR images is a difficult problem due to the presence of speckle which can be modeled as strong, multiplicative noise. The proposed algorithm consists of evolving simple closed planar curves within an explicit correspondence between the interiors of curves and regions of segmentation to minimize a criterion containing a term of conformity of data to a speckle model of noise and a term of regularization. Results are shown on both synthetic and real images.
Ben Ayed
Ismail
I
Institut National de la Recherche Scientifique, INRS-EMT, 800, de La Gauchetière Ouest, Montréal, QC, H5A 1K6, Canada. benayedi@inrs-emt.uquebec.ca
Mitiche
Amar
A
Belhadj
Ziad
Z
D000465:Algorithms; D001185:Artificial Intelligence; D016000:Cluster Analysis; D003198:Computer Simulation; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D015233:Models, Statistical; D009716:Numerical Analysis, Computer-Assisted; D010363:Pattern Recognition, Automated / Q000379:methods*; D011825:Radar; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity