基于自适应模板的图像修复算法

当前基于纹理的图像修复算法中模板块的尺寸是固定的,这样,当模板块尺寸很小时,虽然修复的精度会提高,但是算法的时间复杂度会大幅增加;相反,当模板块尺寸很大时,虽然可以降低算法的时间复杂度,但会使算法的误修复率提升。针对以上问题,提出了基于自适应模板的图像修复算法,该算法能够根据当前模板块与尺寸扩大后模板块之间的灰度均值及方差的变化情况来自适应地扩大模板尺寸,同时,根据模板块与样本块之间的匹配情况自适应地缩小模板块。最后,将所提提出的算法用于实例验证,其结果表明所提算法不但可以有效地提高图像修复的精度,而且提高了图像修复的效率

Image inpainting algorithm based on adaptive template

Currently, template size of texture-based image inpainting algorithm is fixed. Therefore, when the template size is small, the inpainting accuracy improves, but time complexity increases substantially; on the contrary, when the size is large, the time complexity declines, but inpainting error rate increases significantly. Adaptive template size algorithm proposed in this paper can enlarge template size according to the change of expect and variance of grayscale value between current template and its expanded one. Meanwhile, this approach can reduce template size according to the match degree between template and exemplar. After adaptively determining the template size, texture-based image inpainting algorithm was improved and used in experiments. The experimental results show this approach can highly improve the inpainting accuracy with high efficiency.