Image segmentation active contour model based on nonlocal total variation
基于非局部总变差的图像分割活动轮廓模型*

Based on the continuous global minimizing method for the general active contour model, this paper proposed a nonlocal active contour model having continuous global minimizing solutions by using four nonlocal total variation. Due to the nonlocal property of the model proposed here, noise could be effectively removed in the course of segmentation, and the repeated fine structures could be preserved simultaneously. Numerical experiment shows this model can segment the main structures and the fine structures very well, however many small fine structures are lost in the results of the standard active contour model.