自适应样本块大小的图像修复方法

Image completion method with adaptive patch size

传统基于样本块的图像修复算法中样本块大小是固定不变的,在修复过程中无法根据图像的具体情况进行调节,这在很大程度上影响了图像的整体修复效果。为了解决这一问题,提出一种自适应确定样本块大小的方法。该算法通过分析图像的梯度域变化,获得各像素点处的结构信息,进而自适应确定待修复样本块的大小。仿真实验结果表明,该算法能够有效克服传统方法中经常出现的诸如结构误传播、图像整体结构丢失等缺点,对具有明显结构变化的图像取得了比较理想的修复效果。

In the traditional examplar-based algorithm, the image completion effect is greatly degraded due to the fixed patch-size, which cannot change together with an image automatically in the process of completing. So in this paper we propose an adaptive patch-size determining method to solve this problem. By analyzing the image changes in the gradient domain, this method acquires the structure information of each pixel, and then automatically adjusts the patch-size. The simulation results show that this method can overcome many shortcomings of traditional methods, such as structural error propagation and whole structure loss, and realizes perfect completion effect for images with obvious changed structure.