水平集的图像分割方法综述

图像分割是图像处理中的关键技术之一,Osher和Sethian提出的水平集方法有效地解决了以前算法不能解决在曲线演化过程中的拓扑变化问题。目前,基于水平集方法的图像分割算法很多,对于不同应用领域的图像处理问题,人们都提出了相应的解决方法,而且大量的研究者还在不断改进和提高这些算法的效率和有效性。因此,本文按照水平集算法在图像分割中应用的发展历程将其分为3种情况进行了综述,以此为该领域读者提供借鉴。

Level Set Methods and Its Application on Image Segmentation

Image segmentation is a key problem in image processing. Curve evolution, which is very difficult to solve previously,was effectively handled by level set method proposed by Osher and Sethian. At present, there are so many image segmentation methods based on level set, and there are different methods to different images. Now, these methods are continually improved to enhance the speed and the veracity. So in this paper, according to the development of the image segmentation methods based on level set, this algorithm is introduced for readers of different backgrounds in this field to use.