基于曲率约束因子与边缘加权法则的图像修复算法

针对当前较多图像修复算法主要通过对图像块进行方差和度量的方法来完成图像修复,忽略了图像块的显著边缘特性,使得修复图像容易出现模糊效应以及不连续效应等不良现象,导致算法修复性能不佳的不足,提出了基于曲率约束因子耦合边缘加权法则的图像修复算法.首先,通过像素点的等照度线方向构造曲率约束因子,对数据项进行约束,形成优先级度量函数,利用优先级度量函数选取优先修补块;然后,利用像素点的均值之差构造像素自相关模型,对样本块的大小进行了调整;最后,以样本块显著边缘为约束,构造了边缘加权模型,通过边缘加权模型联合SSD(sum of squared differences)模型建立了边缘加权法则,对最优匹配块进行搜索,用于对待修补块进行修复.仿真实验结果表明,与当前图像修复算法相比,本文设计的图像修复算法修复的图像具有良好的视觉效果.

On Image Inpainting Algorithm Based on Curvature Constraint Factor and Edge Weighted Rule

In view of the current image restoration algorithm more mainly through variance and measurement method of image block to complete image restoration,ignoring the significant edge characteristics of image block,the image restoration effect and not prone to fuzzy continuous effects and other undesirable phenomena,resulting in poor performance of the repair algorithm.In this paper,a research of image inpainting algorithm based on curvature constraint factor and edge weighted rule has been proposed.Firstly,the curvature constraint factor has been constructed through the pixel''s luminance direction,and the data item has been constrained to form a priority measurement function,and the priority patch block been selected by the priority measurement function.Then,the pixel autocorrelation model has been constructed by the difference between the mean values of the pixels,and the size of the sample block been adjusted.Finally,the edge weighted model has been constructed by taking the salient edge of sample block as constraint.Through edge weighted model combined with SSD model,the edge weighting rule has been established,and the optimal matching block been searched to repair the patch block.Simulation results show that compared with the current image inpainting algorithm,the image inpainting algorithm designed by this paper has a good visual effect.