SAR image segmentation algorithms based on I-divergence-TV model
Guangming Liu Quanying Sun Qi iu
In this paper, we propose a novel variational active contour model based on
I-divergence-TV model to segment Synthetic aperture radar (SAR) images with
multiplicative gamma noise, which hybrides edge-based model with region-based
model. The proposed model can efficiently stop the contours at weak or blurred
edges, and can automatically detect the exterior and interior boundaries of
images. We incorporate the global convex segmentation method and split Bregman
technique into the proposed model, and propose a fast fixed point algorithm to
solve the global convex segmentation question[25]. Experimental results for
synthetic images and real SAR images show that the proposed fast fixed point
algorithm is robust and efficient compared with the state-of-the-art approach.