一种改进的灰度图像修复算法

针对大面积破损区域图像修复中Criminisi算法存在修复质量差和时间复杂度高的缺点,提出一种改进的图像修复算法。改进算法将优先权的计算形式由相乘变为相加,并增加梯度数据项对优先权的计算方式。通过结构信息控制优先权,从而优先修复结构信息。设计根据待修补块中心点的梯度大小,使用全局搜索来寻找匹配块,以提高修复质量和速度。对置信度更新的方式进行修正,引入每次匹配的精度作为惩罚因子的参数,以减小误差向下一次迭代的传播。仿真实验显示,改进算法的修复效率比原算法提升了58%到70%,且修复质量的视觉效果有所提升。

An improved gray-scale image inpainting algorithm

Due to shortcomings of the Criminisi algorithm for inpainting large area damaged image with poor repair quality and high time complexity,an improved image inpainting algorithm is presented in this paper.The improved algorithm changes the form of calculation for priority from multiplication to addition,and adds the gradient data to calculate priority.In this algorithm,the priority is controlled by the structure information,and therefore the priority is also given to in-paint structure information.The gradient magnitude of the center of the block to be inpainted is used to improve the quality and speed of inpaint in order to global search for the matching block. The error propagation to the next iteration is reduced by amending the update mode of confidence and introducing matching accuracy each time as parameters of the penalty factor.Simulation ex-periments show that the improved algorithm can increase inpaint efficiency from 58%to 70%and has better reconstruction quality from the visual effect compared to the original algorithm.