摘要
在分析几种关键图像修复算法的实现原理、适用性及其优劣的基础上,针对目前图像修复算法可能存在适用性有限、优化修复算法中存在的算法复杂度较高或者未考虑破损图像的结构信息的情况,提出了一种基于数据融合的加权均方差快速增强图像修复算法,并将其应用于壁画和自然图像的修复实验中。通过系统仿真实验证明,在修复强结构纹理自然图像和壁画时该方法能紧密结合图像结构信息进行有效地修复,同时,其适用性在原有的基础上有所提高。
On the basis of analysis of several key image inpainting algorithms about implementation principle,applicability and superiority,considering their limited applicability,higher complexity and failured to take into account the structure information of damaged images,a new faster inpainting algorithm using structure and texture optimization was proposed,which is based on the fast marching method for weighted mean squared error and data fusion of Dempster-Shafer evidence theory applications.This technique can be used in reconstruction of damaged portions of ancient painting and also in removing entire objects from natural image.Through repairing the murals and natural images,the effectiveness of the proposed algorithm was verified by means of image completion and system simulation experiment.The proposed algorithm considers the structure information,achieves better repairing results and improves applicability.
出处
《图学学报》
CSCD
北大核心
2015年第2期233-237,共5页
Journal of Graphics
基金
国家自然科学基金资助项目(61461046
21463023
61261042)
甘肃省高等学校基本科研业务费资助项目(2050205)
天水市中青年科技支撑资助项目(TSK1201)
天水师范学院中青年教师科研资助项目(TSB1108)
关键词
数据融合
均方差
图像修复
算法
data fusion
mean squared error
image inpainting
algorithm
