Abstract
Many defects now appear in ancient murals due to both natural and man-made factors. To better repair the damaged ancient murals, this paper improves the existing intelligent restoration method. It identifies and marks the crack-producing area, categorizes the mural image into two types – texture area and flat area according to the local gradient features, decides the initial sample block and calculates the weight, analyzes the extracted pixel data and applies discrete differential algorithm to supplement image defects. Through experiments, the method is validated in meeting the needs of image continuity law and human vision. It can shorten the repair time and restore mural cracks in an intelligent way.
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