摘要
该文对Chan-Vese提出的基于Mumford-Shah模型的水平集分割图像的算法做了两方面的改进:首先改进了C-V方法的偏微分方程,使得C-V方法可以快速计算出全局最优分割;其次,采用源点映射扫描方法来快速计算符号距离函数,克服了常规水平集方法中构造符号距离函数计算量大的缺点,并结合该文所提出的基于快速步进法生成符号表的方法,进一步提高了计算稳定性.两方面的改进提高了计算的速度和分割效果,试验统计结果显示,对于512×512的大幅图像,一般只需要10次左右的迭代就可以得到最优的分割效果.对合成图像、生物医学图像的分割结果表明了本文方法的稳健、快速.
A new level set PDE based on the simplified Mumford-Shah model for image segmentation was proposed by Chan and Vese, which shows less insensibility of initialization and noise affect, and has the ability of detecting both inner and outer edges of targets with inner hole just by one enclosed active contour. However, the edges far way from the active contours would be seriously suppressed by the dirac function in the proposed PDE. To solve this problem, this paper improved the C-V's PDE by replacing the dirac function δεE(φ) with |(?)φ| , which eliminates the suppression against the edges wide of the active contours, such that the improved PDE gives global optimization of Mumford-Shah model and need less evolution loops than that of the C-V's PDE. Besides, in order to further stabilize and fasten the level set evolution procedures, the paper addresses an improved approach to construction of the signed distance function using Voronoi source scanning method, which extends the Voronoi source of the grids nearest to active contours to the far grids along with characteristic lines, only needs simple comparison and few multiplication operations with computational complication O(N), faster than the traditional approaches. At last, a new sign map labeling method is proposed to distinguish the inside and outside of the 2D closed active contour by fast marching method. These three improvements dramatically give more efficiency and performance than the C-V approach, for example, typically all edges of an 512×512 large image will be picked up only within 10 iterating times by one initial active con-tour. The segmentation tests for synthesized and biomedical images prove the proposed segmenting method is very fast and robust.
出处
《计算机学报》
EI
CSCD
北大核心
2002年第11期1175-1183,共9页
Chinese Journal of Computers
基金
本课题得到国家自然科学基金(60072026
69931010)资助
