Exploiting local intensity information in ChanVese model for noisy image segmentation
This manuscript presents an improved region-based active contour model for noisy image segmentation. We define a local energy according to intensity information within the neighborhood of each point in image domain. By introducing a kernel function, our method employs intensity information in local region to guide the motion of active contour. Experiments on synthetic and real world images show that our model is robust to image noise while preserving the segmentation efficacy.
noisy image segmentation robust chanvese model level set method variational method