Research on color restoration of faded mural images can promote the protection and display of murals.Color restoration of mural images aims to restore the fading color areas of degraded mural images to their original colors.With the conventional color restoration method based on a single reference mural image,selecting reference mural images similar to degraded mural images is difficult,which in turn affects the quality of color restoration.To this end,a color restoration method based on dual reference optimization is proposed for mural images.The dual reference strategy involves using two reference mural images to restore the color of degraded mural images.The image optimization module is used to suppress the common multiple degradation such as noise and scratches in faded mural images.The encoder-decoder network is used to encode and extract multi-scale features of mural images,whereby a feature fusion module is constructed to optimize the multi-scale features of mural images.A dual reference guidance module is used to calculate the semantic correspondence confidence between the reference and degraded mural images,to achieve similarity matching between image regions for the style fusion of two reference mural images.On this basis,fusion features are utilized to achieve color restoration of degraded mural images.The experimental results show that this method can accurately restore the color of degraded mural images while maintaining the original edge structure information.Non-reference image quality evaluation indicators are used to objectively evaluate the restored mural images of each method.This method reduced the objective evaluation indicators up to 12.2%,on the comparison methods considered.
国家科技期刊平台
NSTL
维普
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