基于八邻域的自适应高阶变分图像修复算法

Image Inpainting Algorithm Based on Adaptive High Order Variation in Eight Neighbors

针对传统的变分偏微分图像修复算法的信息利用不充分、纹理被破坏及人工干预较强等问题,提出一种基于八邻域的自适应高阶变分图像修复算法。该算法充分利用受损图像待修复点像素的八邻域信息,将其分为两组四邻域,在每组四邻域中分别采用非线性各向异性扩散方式进行扩散。通过自适应方法确定每组四邻域中利于修复的最佳p值,根据中心差分方法进行离散化后,最后利用加权平均的方式获得受损图像的高斯-雅克比修复迭代式。仿真实验结果表明,与近几年的一些图像修复算法相比,该算法获得的图像具有良好的评价,PSNR值和SA值最高、修复时间较短、纹理结构与原始图像最接近。

To solve the problems of traditional variation inpainting algorithms,like insufficient information utilization,destroyed texture and strong artificial interference,an adaptive high order variational image inpanting algorithm based on eight neighbors is presented.Firstly,it makes full use of eight neighbors at the points to be repaired in damaged images and divides them into two groups of four-neighbor,then repairs images by nonlinear anisotropic diffusion in each four-neighbor respectively.The optimal value of parameter p in every four-neighbor will be determined by adaptive method.Then those points will be discreted through the central difference method.Finally,the Gauss-Jacobi Iteration of the damaged images can be obtained by using weighting and averaging.Compared with the image inpainting algorithms in recent years,the simulation results show that,the images obtained by the proposed algorithm have good evaluations.Not only is the repair time reasonable,but the texture structure is closest to the original images and values of PSNR or SA are the highest.