基于加权优先级和分类匹配的图像修复方法

An image inpainting method based on weighted priority and classification matching

待修复像素优先级的计算及最佳匹配块的确定是基于纹理合成图像修复方法的两个基本环节,传统方法不仅难于确定优先级计算中的置信度,而且难于搜索到最佳匹配块。提出了一种基于加权优先级和分类匹配的图像修复方法,该方法在优先级模型中,引入指数函数和正规化函数分别优化置信度和数据项,使得计算的优先级更加客观,从而使修复顺序更加合理。基于此,将结构信息作为搜索匹配块的一个度量因子,采用分类筛选方式,选取最佳匹配块。实验结果表明,所提方法在获得良好修复效果的前提下缩短了修复时间。

The calculation of the priority of the pixel to be repaired and the determination of the best matching block are based on two basic steps of the texture synthesis image inpainting method. The traditional method is not suitable because it is difficult to determine the confidence in the priority calculation, and it is difficult to search for the best matching block. An image inpainting method based on weighted priority and classification matching was proposed. In the priority model, the exponential function and the normalization fimction were introduced to optimize the confi- dence and data items separately, the further benefit of which was a more objective priority of calculation and a more reasonable repair order. Based on the proposed functions, the structure information was used as a measure factor of the search matching block, and the best matching block was selected by the classification and screening method. Ex- perimental results show that the proposed method can shorten the repair time under the condition of obtaining good repair effect.