目的 针对基于样本块的图像修复方法容易引起填充前沿的锯齿效应，分阶段修复方法对优先权的约束性不足等问题，提出基于样本块搜索和优先权填充的弧形推进图像修复方法。 方法 首先对图像进行均值滤波操作，以更精确地计算等照线；再加入局部特征信息，进一步约束优先权，使修复的顺序更加合理；度量最佳样本块，加入梯度信息减少候选块的个数；分级搜索样本，平衡时间效率和空间搜索效率；最后弧形推进填充，保持边缘的平滑性。结果 将本文方法与其他方法进行修复结果对比分析。主观上，本文方法的修复结果视觉连通性较好；客观上，峰值信噪比（PSNR）的值均高于其他修复方法。结论 本文方法不仅可以较好地修复自然图像和文物图像，在目标物移除方面也有很好的应用。修复效果好，适用性强。

Objective Due to the problem that image inpainting method based on the exemplar easily leads to sawtooth in the filled frontier and because the stage-wise inpainting strategy does not provide sufficient constraints on the priority of patch-filling, we propose an inpainting method based on arc promoting, exemplar searching and priority computation. Method Firstly, we carry out the mean filtering operation to calculate the isophotes more precisely. Second, we add the local feature information to further restrict the definition of priority and make the patch-filling order more reasonable. Third, we measure the candidate exemplar patches by adding gradient information, which can decrease the number of candidate patches. Fourth, we search the exemplar patches hierarchically to balance time efficiency and space efficiency. Finally, we fill the target region using an arc promoting method to keep the edge smooth. Result The inpainting result analysis of our method is contrasted with the analysis based on other methods. Subjectively, the method can maintain visual connectivity. Objectively, the value of the peak signal-to-noise ratio (PSNR) were higher than other inpainting methods. Conclusion Not noly can the method be used to repair the images of natural and cultural relics, but also it has good application in the removal of the object. The repair effect is good, and the applicability is strong.