摘要
通过对图像分割与图像抠图的比较和分析,从图划分的角度考虑抠图问题,提出一种具有纠偏性的图像抠图的全局优化方法.该方法在最小化前景对象与背景相互分离的软分割开销的同时,最大化前景对象的内部关联度.理论分析和实验结果表明,与其他形式的抠图优化目标函数相比,文中方法能够更有效地提取出全局最优的抠图结果,有利于实现自动或半自动的抠图处理.
A global algorithm of optimization of deviation rectification for image matting is presented, which treats the process of image matting as that of graph partition after carefully comparing image segmentation with image matting. While minimizing the cost of soft segmentation between foreground object and background, the approach can maximize the degree of association among the foreground object and background, the approach can maximize the degree ot association among the Ioreground objects. Both theoretical analysis and experimental process are studied to demonstrate that the proposed method can be more efficient to extract global optimal matte compared with other function expressions of matting optimization. This research will have a contribution to the implementation of automatic or semi-automatic matting.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2010年第2期264-271,共8页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(60673027)
国家自然科学基金国际合作项目(60811140344)
武汉大学自主科研新兴交叉科学研究项目
武汉大学博士研究生科研自主基金
关键词
图像抠图
优化目标函数
全局最优
谱抠图
image matting
optimization object function
global optimization
spectral matting
