In recent years， the research on color restoration of mural image has become a hot issue in the fields of mural cultural heritage protection and display. Aiming at the problems that the overall feature information of mural image color restoration is difficult to extract and maintain effectively， and local color restoration is prone to generate false color phenomenon and color spill， a multi-level color restoration method of mural image based on gated positional encoding was proposed. Firstly， an encoder network based on global feature constraints was constructed， and the global feature gradient of the image was extracted as the downsampling value standard by an improved multi-kernel maximum-average-minimum pooling algorithm to establish the mural image feature pyramid， so as to reduce the overall feature loss of the mural image in the feature coding process. Secondly， in order to restore the local color information of mural image accurately， a color transfer module based on gated positional encoding was designed to restrict the learning of similarity kernel between content feature and color feature in spatial domain for accurately mapping of color feature in the mural image to be restored， so as to reduce false color phenomenon and color spill in restored image. Experimental results show that compared with the mural restoration images generated by AdaIN （Adaptive Instance Normalization）， AST （Arbitrary Style Transfer） and other comparison methods， the NIQE （Natural Image Quality Evaluator） and PIQE （Perception based Image Quality Evaluator） in the mural restoration images generated by proposed method achieve the best results. It can be seen that the proposed method has good performance in restoring the color information of mural image and maintaining the global structural and textural characteristics of the mural image to be restored.
