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In order to overcome the current image restoration algorithms mainly rely on the image confidence information to obtain the priority repair block, ignoring the image energy information, making the algorithm"s repair performance decline, resulting in the repair image discontinuity and pseudo Gibbs phenomenon and other defects. In this paper, energy information and gradient adjustment mechanism are used to repair the image. Firstly, the energy information of the image is obtained by the region energy function, and the priority information of the block to be repaired is calculated by the data and confidence terms. Then, on the basis of image gradient modulus, a gradient adjustment mechanism is established to adjust the size of the sample block and obtain the sample block size corresponding to the image texture. Finally, the sum function of square difference is introduced to calculate the similarity between the block to be repaired and the matching block, so as to obtain the optimal matching block. Through the difference between pixels, construct the similarity penalty factor to update the confidence term and complete the image restoration. The experimental results show that the algorithm in this paper has better performance than the current algorithm, better texture coherence and good structural similarity.