基于样本的图像修补

提出了一种基于样本的图像修补方法。该方法首先计算填充前缘上每个修补块的优先权,确定填充前缘上最高优先权的修补块;然后在样本区域中寻找最高优先权修补块的最佳样本块,拷贝最佳样本块的有关图像数据到最高优先权修补块的未填充好的像素点位置;再更新这些刚填充的像素点的自信度。重复这些步骤直至整个图像受损区域填充修补完毕。实验结果表明,该方法能同时有效地修补图像受损区域的纹理和结构,还能较好地去除图像上不需要的物体。

Exemplar-Based Image Inpainting

In this paper, a method of exemplar-based image inpainting is proposed. First,the priority of each patch on the "fill front" should be calculated, and the patch with the highest priority is obtained. Then, the best exemplar patch corresponding to the patch with the highest priority is discovered in the exemplar region, and the relevant data is copied from the best exemplar patch to the unfilled parts of the patch with the highest priority. Finally, the confidence values of pixels which have been filled just now are updated. The whole damaged region will be fully filled through iterating the above steps. Experimental results indicate that the method can be well effective to fill the texture and structure of the damaged areas of image simultaneously, and to remove the undesired objects on images.