Image Processing for Virtual Restoration of Artworks
IEEE MultiMedia
A region growing and merging algorithm to color segmentation
Pattern Recognition
Digital color restoration of old paintings
IEEE Transactions on Image Processing
Proceedings of the 2010 conference on Information Modelling and Knowledge Bases XXI
Color changing and fading simulation for frescoes based on empirical knowledge from artists
PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
Restoration of X-ray fluorescence images of hidden paintings
Signal Processing
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This paper proposes a novel scheme to virtually restore the colors of ancient murals. Our approach integrates artificial intelligence techniques with digital image processing methods. The knowledge related to the mural colors is first categorized into four types. A hybrid frame and rule-based approach is then developed to represent knowledge and to infer colors. An algorithm that takes into account color similarity and spatial proximity is developed to segment mural images. A novel color transformation method based on color histograms is finally proposed to restore the colors of murals. A number of experiments based on real images have demonstrated the validity of the proposed scheme for color restoration.