摘要
传统基于样本块的图像修复方法是在图像全局区域内循环搜索最优相似块,且结构传播过程易受置信因子影响,使得算法运算量大、时间长、效率低.针对以上问题,提出基于随机映射的修复算法.该算法采用随机映射的方法搜索与待修复区域在结构和纹理相似的样本区域,去除冗余的样本搜索空间;其次优化了基于置信因子和边缘信息的优先级计算方法,改进了最优相似块的计算方法,增强了图像结构传播的正确性.实验结果表明,该方法的修复速度比传统方法提高了5～10倍,且增强了图像修复效果.
The traditional patch-based image completion algorithms circularly search the most similar patches in the whole image, and are easily affected by confidence factor in the process of structure propagation. As a result, these algorithms have poor efficiency and need a lot of time for the big computation. To overcome these shortages, a fast image completion algorithm based on randomized correspondence was proposed. It adopted a randomized correspondence algorithm to search the sample regions, which have similar structure and texture with the target region, so as to reduce the search space. Meanwhile, the method of computing filling priorities based on confidence factor and edge information was optimized to enhance the correctness of structure propagation. In addition, the method of calculating the most similar patches was improved. The experimental results show that, compared with the traditional algorithms, the proposed approach can obtain 5 - 10 times speed-up in repair rate, and performs better in image completion.
出处
《计算机应用》
CSCD
北大核心
2014年第6期1719-1723,共5页
journal of Computer Applications
基金
国家自然科学基金资助项目(60771065
51378365)
关键词
图像修复
近似邻域
纹理合成
结构传播
image completion
approximate neighborhood
texture synthesis
structure propagation
