最大流方法在图像去噪和分割中的研究进展
Progress of Max-Flow Method in Image Denoising and Segmentation
DOI: 10.12677/jisp.2013.22003, PDF, HTML, 下载: 3,538  浏览: 12,957  国家自然科学基金支持
作者: 王小欢*, 杨晓艺, 宋锦萍:河南大学数学与信息科学学院,开封
关键词: 最大流图像去噪图像分割Max-Flow; Image Denoising; Image Segmentation
摘要:  近年来,基于能量泛函的图像去噪和分割模型得到广泛的关注,解决这类模型的有力工具之一是最大流方法。本文分别介绍离散的和连续的最大流方法,包括能量泛函最小化问题转化为最大流问题的基本步骤,以及相应最大流问题的求解方法,并展望最大流方法的发展前景。
Abstract: In recent years, image denoising and segmentation model based on energy functional received widely atten- tion. Max-flow method is one of the most powerful tools to solve this kind of model. Discrete and continuous max-flow methods are introduced, they both include the basic steps in which energy functional minimization problem transformed to max-flow problem, and the solutions of the corresponding max-flow problem are also reviewed. In addition, the de- velopment of max-flow method are also discussed.

文章引用:王小欢, 杨晓艺, 宋锦萍. 最大流方法在图像去噪和分割中的研究进展[J]. 图像与信号处理, 2013, 2(2): 19-23. http://dx.doi.org/10.12677/jisp.2013.22003

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