Variational image segmentation in presence of multiplicative gamma noise

A variational active contour model to segment images corrupted by multiplicative gamma noise is proposed. Inspired by the well-known AA model, a new energy functional is derived to attract the contour to the true boundary. Split Bregman methods are adopted to resolve the corresponding energy minimisation problem. Experimental results for synthetic and real images show that the proposed algorithm is very efficient and effective.