Active contour model for images corrupted by multiplicative noise with rayleigh distribution
Guodong Wang, Zhenkuan Pan, Jie Xu, Zhimei Zhang, Cunliang Liu, Jieyu Ding · 2011
Multiplicative noise are often exist in real images especially in medical images. So segmentation is a hard work with this noise. In this paper, we propose a new active contour model coupling multiplicative noise removing model for multiplicative noisy image segmentation. In this paper, we only concern multiplicative noise with rayleigh distribution which is often occurred in such as ultrasound images. Our model can segment the target in these images. Finally, a fast method called Split Bregman method is used for the segmentation implementation. The performance of our method is demonstrated on a variety of synthetic and real ultrasound images.