International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
IEEE Computer Graphics and Applications
Example-Based Super-Resolution
IEEE Computer Graphics and Applications
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Color transfer in correlated color space
Proceedings of the 2006 ACM international conference on Virtual reality continuum and its applications
Image Denoising Via Learned Dictionaries and Sparse representation
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
On single image scale-up using sparse-representations
Proceedings of the 7th international conference on Curves and Surfaces
-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
IEEE Transactions on Signal Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries
IEEE Transactions on Image Processing
Inverse halftoning and kernel estimation for error diffusion
IEEE Transactions on Image Processing
Histogram-Based Prefiltering for Luminance and Chrominance Compensation of Multiview Video
IEEE Transactions on Circuits and Systems for Video Technology
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There are numerous approaches towards restoration of art, including computer applications as aid to manual performance. However, to our knowledge, it has not been attempted to recuperate high quality images of missing or presumably destroyed works of art. While these works will never again be available in their original form, it may be feasible to considerably enhance the quality of preserved photographic reproductions. A pioneering combination of super-resolution and colour correction is presented here, targeting the reclamation of high quality images of lost works of art. The techniques are performed by example, utilising correspondence between artworks of similar nature, currently available both in low and high quality. With extensive prior knowledge in the domains of super-resolution and colour correction, selected approaches were studied, implemented and tested, concluding to the most efficient. Experimental results are highly promising, revealing a new research path in colour imaging for fine art.