Fast SAR image segmentation method based on grey fuzzy entropy
于灰色模糊熵的SAR图像快速分割方法*

Aiming at the special character of noise in SAR image, this paper presented a fast SAR image segmentation method based on grey fuzzy entropy, in which not only utilized the gray level information of each pixel, but also involved its spatial correlation information within the eight neighborhood pixels. To decrease the noise-sensibility of the traditional fuzzy entropy methods, it introduced the theory of grey relational analysis to modify the existing fuzzy membership function by selecting the referential sequence and the compared sequences from the original image, and then employed the grey correlation degree of the two kinds of sequences to better the membership function. Consequently, designed a grey fuzzy entropy function to locate the best segmenting threshold. In addition, used PSO, as an swarm intelligent tool, to speed up the segmenting procedure. Some experimental results indicate that the method not only ignores the disturbance of inherent speckle in SAR image, but also provides with some better segmented objects.