Image completion is an approach to fill a damaged region (hole) in an image. In this study, we adopt a novel method which can repair a target region with structural constraints in an architectural scene. An objective function that consists of three terms is proposed to solve the image completion problem. In color term, we compute a parameterized transformation model using detected plane parameters and measure the distance between the target patch and transformed source patch. This model helps to extend the patch search space and find an optimal solution. To improve the patch matching accuracy, we add a guide term that includes structure term and consistency term. The structure term encourages sampling patches along the structural direction, and the consistency term is used to maintain the texture consistency. Considering the color deviation between patches, we add a gradient term into a framework that can solve more challenging problems. Compared with previous methods, the proposed method has good performance in preserving global structure and reasonably estimating perspective distortions. Moreover, we obtain acceptable results in natural scenes. The experimental results illustrate that this novel method is a potential tool for image completion.

图像完成是一种填充图像中受损区域（孔）的方法。在这项研究中，我们采用了一种新颖的方法，该方法可以修复建筑场景中具有结构约束的目标区域。提出了由三项组成的目标函数来解决图像完成问题。在颜色方面，我们使用检测到的平面参数来计算参数化的转换模型，并测量目标面片和转换后的源面片之间的距离。该模型有助于扩展补丁搜索空间并找到最佳解决方案。为了提高补丁匹配的准确性，我们添加了一个指导术语，其中包括结构术语和一致性术语。结构项鼓励沿结构方向采样斑块，而一致性项则用于保持纹理的一致性。考虑到色块之间的颜色偏差，我们将梯度项添加到可以解决更具挑战性的问题的框架中。与以前的方法相比，该方法在保留全局结构和合理估计透视畸变方面具有良好的性能。此外，我们在自然场景中获得可接受的结果。实验结果表明，该新颖方法是实现图像完成的潜在工具。