摘要
目的提出一个算法,使计算机能够自动修复破损区域较大且结构信息较复杂的图像。方法通过模仿手工修复破损区域较大且结构信息较复杂的图像的方法,按以下2个步骤来修复图像:1)破损区域的划分,首先,对各断裂边界线进行匹配配对,然后,将已配对的各断裂边界线进行直接连接,从而在破损区域内形成各个待修复块;2)各块的修复,首先,采用Bertalmio,Sapiro,Caselles,Ballester(BSCB)算法中的传输方程和扩散方程将已选邻域信息迭代传输和扩散到各块破损区域,以修复完优先级最大的各个块,然后,判断是否有次优先级的待修复块,若有,则采用边界线删除算法删除部分冗余边界线,接着按相同方法修复次优先级的待修复块,若无,则修复完成。结果基于以上图像修复步骤,提出了破损区域分块划分的图像修复算法。将该算法和其他3个算法用于修复破损区域较大且结构信息较复杂的图像,其结果显示,该算法所修复图像的峰值信噪比(PSNR)值平均提高1.49 dB,同时,所修复图像具有较好的视觉效果。结论和其他3个算法相比,本文破损区域分块划分的图像修复算法更适合于修复破损区域较大且结构信息较复杂的图像。
Objective To propose an image inpainting algorithm that can enable the computer to repair images with a larger damaged area and more complex structure information. Method Images with a larger damaged area and more complex structure information are repaired by imitating manual repair methods, and it has two steps ： the division of damaged area and the repair of each block. 1 ） In the division process of the damaged area the matching degree of every two damaged boundaries are calculated first and the boundaries having the greatest matching degree are made into matching pairs. Then, the well- matched boundaries are directly connected, dividing the damaged region into different blocks. 2） In the repair process of each block, the transmission equation and diffusion equation of the BSCB algorithm are used to repair each block with the highest priority first. Second, our algorithm judges whether there is a block with second priority to be repaired, if yes, the boundary deletion algorithm is used to delete the redundant boundary lines, and the same method is used to repair each block ; if not, the repair process is completed. Result Based on the above image inpainting steps, an image inpainting algorithm based on partition block of damaged region is proposed. The experimental results show that the proposed method can increase the PSNR value about 1.49 db and achieve better visual effect. Conclusion The proposed algorithm is more suitable for repairing damaged images with a larger damaged area and more complex structure information compared with other three image inpainting algorithms.
出处
《中国图象图形学报》
CSCD
北大核心
2014年第6期835-842,共8页
Journal of Image and Graphics
基金
国家社会科学基金项目(12EF119)
西藏自治区重点科技计划项目(Z2013B28G28/02)
国家级大学生创新创业训练计划项目(201210694019)
关键词
图像修复
手工修复
边界线
BSCB算法
结构信息
image inpainting
manual inpaiting
boundary lines
BSCB algorithm
structure information
