Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
531558 | Pattern Recognition | 2008 | 9 Pages |
Abstract
A method toward unsupervised segmentation of synthetic aperture radar (SAR) images is proposed. In this method, the distribution of SAR intensity image and the maximum a posteriori (MAP) algorithm is used to obtain an initial segmentation. Then according to the equivalence between the solid heat diffusion model and image scale-space, multiscale anisotropic smoothing of the posterior probability matrixes is introduced to remove the influence of speckle and to preserve important structure information. The effectiveness of this algorithm is demonstrated by application to simulated and real SAR images.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Gui Gao, Lingjun Zhao, Jun Zhang, Diefei Zhou, Jijun Huang,