为了对大规模目标区域的图像进行修复，提出了一种既能保持线性特征和纹理信息，又能应用于大规模目标区域的基于模块的图像修复模型。该模型首先使用像素切向等照度线强度约束修复优先级，由于切向等照度线方程在图像边缘宽度约束下扩散，因此具有很好的线性特征保持性能。这种扩散具备形态学不变性，可修复自然场景图像；然后采用Euclidean距离计算模块相似度，并加入偏微分方程约束，使得线性特征位置的像素点在匹配中影响较大；使用散度约束下总体变分插值法对修复结果进行无接缝效应处理，使得最终修复结果平滑；最后扩展模型相似度函数，使目标区域可被修复为指定的纹理特征。理论和实验结果证明该模型在图像修复中是有效的。

In this paper a novel large target region image inpainting model which can preserve linear structure and texture information is proposed. The model uses a cross isophotes diffusion equation constrain the inpainting order. The cross isophotes equation diffuses considering the edge extent, so the model has good linear structure preserving property. Diffusion of cross isophotes is morphologically invariant and it can fill the target region of the natural scene very well. The euclidean distance is used as the similarity function, while the partial differential equation constraint which is used to enlarge the effect of pixels in linear structure is employed. To reduce the seams caused by this model, and achieve a seamless image, a total variation interpolation constrained by gradient is used in the inpainted result. At last the similarity function is extended, and the target region can be inpainted to the assigned texture. Both theoretical analysis and experiments have verified the validity of the new model.