针对目前贪婪修复算法可能存在修复效果视觉不一致以及优化修复算法中存在的算法复杂度较高或者未考虑结构信息的情况，提出一种基于加权优化的图像修复算法，通过定义出新的能量函数，把图像破损修复问题转化为加权的离散优化问题，在保证结构信息强、信任度高的区域被优先修复的前提下，利用贪婪修复思想获取初值并计算权值，然后通过类EM算法迭代求解出破损区域中每一个像素的最佳值。与其他贪婪合成和最优化方法相比，优先考虑结构信息对修复效果的影响，更好地保持了纹理和结构的整体一致性。

Owning to the visual inconsistency of the greedy synthesis algorithm and neglecting of structure information of other optimization based inpainting, a new image inpainting algorithm using structure and texture optimization was proposed. The image inpainting was formulated as minimization of a weighted energy function, which was optimized using an expectation maximization(EM)-like algorithm. To ensure damaged regions with strong structure and high confidence been given priority to restoration, a greedy approach was used to set initial values and to calculate weight values for the EM algorithm. Compared with greedy synthesis and optimization based image inpainting approaches, the proposed algorithm considers the structure information and achieves better repairing results.