摘要
针对能够同时进行图像分割、去噪与重建目的的Mumford-Shah能量泛涵最小值图像模型求解非常困难这一问题,提出了“多层Mumford-Shah图像分割、去噪与重建模型”和求解该多层模型最小值的“咏平集逐层迭代算法”．该多层模型是Mumford-Shah“最小分割问题”的“多层”模型．实验结果表明,该方法不仅能够同时进行具有T型图像边缘或更复杂拓扑结构图像边缘的图像分割、去噪与重建,而且比Tsai A．等人提出的多层求解轮廓和Chan T．等人提出的多相水平集方法更简单更有效．
A novel hierarchical Mumford-Shah functional model is addressed to simultaneously segment,denoise and reconstruct the data within a given image and to handle important image features such as triple points and other multiple junctions, which can be seen as a hierarchical case of the Mumford-Shah minimal partition problem. At the same time, a new iterative tier-by-tier algorithm based on techniques of level set is proposed to minimize the hierarchical Mumford-Shah functional, which is more effective and more simple than existing algorithms such as the hierarchical approach proposed by Tsai A et al. and the multiphase level set methods proposed by Chan T et al.
出处
《自动化学报》
EI
CSCD
北大核心
2006年第4期534-540,共7页
Acta Automatica Sinica
基金
国家自然科学基金(60375001)
教育部高等学校博士点科研基金(20030532004)资助~~
