Fast SAR image segmentation method based on the two-dimensional grey entropy model

In order to speed up the segmentation procedure and solve the problem of noise-sensibility in SAR image segmentation, the paper suggests a fast SAR image segmentation method based on the 2D grey entropy model, which integrates the wavelet transform, Genetic Algorithm (GA), image entropy and grey theory. In the method, after an approximation image and a gradient image are deduced from the original image respectively via the wavelet transform, their concurrence matrix is constructed. On the basis of the matrix, a 2D grey entropy based fitness function is designed for GA. And then, after the operations of selection, crossover and mutation, the best threshold is obtained. Finally, our experimental results indicate that the method not only ignores the disturbance of inherent speckle in the SAR image, but also shortens the segmenting time obviously.