基于结构偏移映射统计和多方向特征的MRF图像修复算法

为使目标移除后的修复效果更好地满足人眼视觉要求，本文提出基于结构偏移映射统计和多方向特征的修复方法.一方面，为更好地保持修复后图像结构部分的连贯性，首先基于Curvelet变换获得的边缘特征将待修复图像划分为结构部分和非结构部分，分别统计相似块之间的偏移映射，在此基础上选择主要的偏移映射作为两部分的候选标签.另一方面，为更好地保持填充区域内相邻像素间的连续一致性，构造引入多方向特征的全局能量优化方程.实验结果表明本文所提出的图像修复算法性能优于多种现有算法.

MRF Image Inpainting Algorithm Based on Structure Offsets Statistics and Multi-direction Features

To make the inpainted images better meet human eye visual requirement,this paper proposes a MRF image inpainting algorithm based on structure offset statistics and multi-direction features.On one hand,to better maintain structure coherence of the inpainted images,the degraded image is partitioned into structure and non-structure parts according to the edge features extracted by Curvelet transform,and the offsets between the similar patches are respectively counted.For each part a few dominant offsets are selected as the candidate labels according to their statistics.On the other hand,to better maintain neighborhood consistence between adjacent pixels,the energy function is constructed by incorporating multi-direction features.Experimental results show that the proposed approach outperforms several state-of-the-art methods.