摘要
为了修复复杂破损区域周边信息模糊不可信及数目较多的敦煌壁画,在充分考虑敦煌壁画自身信息复杂性、壁画修复视觉效果及其修复合理性易受像素修复顺序影响等因素的基础上,提出一种D-S证据理论数据融合方法对修复区域填充算法的优先权函数进行改进的图像修复算法.首先采用D-S证据理论将修复区域边缘目标块的信任因子和数据因子分别转化为基本概率赋值函数,然后对其进行数据融合得到一个新的优先权函数,最后对图像进行修复,得到修复效果较好的壁画.从视觉心理学角度对复杂破损敦煌壁画进行实验的结果表明,该算法是有效的,其克服了Criminisi算法及其改进算法不能很好地修复敦煌壁画的缺点,修复效果较其他改进算法有了显著提高.
In order to repair large numbers of Dunhuang Murals with intricate damaged area and unbelievable vague information, the Dempster-Shafer evidence theory and its data fusion, one algorithm for repairing images, is presented in this paper, which improves the priority function of repair area filling algorithm. It is proposed on the basis of being taking full consideration of information complexity of the Dunhuang Murals, visual effects of mural inpainting, the reasonableness of repair being easily influenced by pixel repair order, and the other factors. Firstly the Dempster-Shafer evidence theory and its data fusion are used to transfer clear factors and data factors in the edge of repaired area separately to their own basic probability value functions, then a new priority function is obtained through fusing data, and finally we will see the perfectly repaired Murals. From the point of view of the visual psychology, the experimental results show that the repairing effect is improved and the effectiveness of the proposed algorithm is much better than those of others. For example, it gets rid of the disadvantage of Criminisi algorithm and its improved algorithm.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2011年第2期284-289,共6页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(60675059)
关键词
敦煌壁画
修复
D—S证据理论
数据融合
优先权计算
Dunhuang Mural
inpainting
D-S evidence reasoning
data fusion
prioritv computation
