Journal of Visual Communication and Image Representation
Knowledge based lacunas detection and segmentation for ancient paintings
VSMM'07 Proceedings of the 13th international conference on Virtual systems and multimedia
An image contrast enhancement method based on genetic algorithm
Pattern Recognition Letters
Visual impact enhancement via image histogram smoothing and continuous intensity relocation
Computers and Electrical Engineering
Image contrast enhancement based on block-wise intensity-pair distribution with two expansion forces
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
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
Gaussian mixture modeling of histograms for contrast enhancement
Expert Systems with Applications: An International Journal
Restoration of X-ray fluorescence images of hidden paintings
Signal Processing
Image contrast enhancement for preserving mean brightness without losing image features
Engineering Applications of Artificial Intelligence
| Hi-index | 0.02 |
This work presents a novel algorithm using color contrast enhancement and lacuna texture synthesis is proposed for the virtual restoration of ancient Chinese paintings. Color contrast enhancement based on saturation and de-saturation is performed in the u'v'Y color space, to change the saturation value in the chromaticity diagram, and adaptive histogram equalization then is adopted to adjust the luminance component. Additionally, this work presents a new patching method using the Markov random field (MRF) model of texture synthesis. Eliminating undesirable aged painting patterns, such as stains, crevices, and artifacts, and then filling the lacuna regions with the appropriate textures is simple and efficient. The synthesization procedure integrates three key approaches, weighted mask, annular scan and auxiliary, with neighborhood searching. These approaches can maintain a complete shape and prevent edge disconnection in the final results. Moreover, the boundary between original and synthesized paintings is seamless, and we are unable to distinguish in which the undesirable pattern appears.