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By Hidehiko Komatsu, Naokazu Goda (auth.), Alain Trémeau, Raimondo Schettini, Shoji Tominaga (eds.)

ISBN-10: 3642032648

ISBN-13: 9783642032646

This booklet constitutes the completely refereed lawsuits of the second one Computational colour Imaging Workshop, CCIW 2009, which used to be held in Saint-Etienne, France, in March 2009.

The 23 revised complete papers, offered including one invited paper, have been conscientiously reviewed and chosen from forty submissions. The papers, which include a complete of 114 coloured figures, are oganized in topical sections on computational colour imaginative and prescient versions; colour fidelity; colour image/video indexing and retrieval; colour photo filtering and enhancement; colour copy (printing, scanning, displays); and multi-spectral, high-resolution and excessive dynamic diversity imaging.

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Additional resources for Computational Color Imaging: Second International Workshop, CCIW 2009, Saint-Etienne, France, March 26-27, 2009. Revised Selected Papers

Example text

1 Introduction It is well established that signals encoded by three classes of cones (L, M and S) are combined at the retina to generate cone-opponent signals, which are then conveyed to the primary visual cortex via the lateral geniculate nucleus (LGN). The retinal and the LGN cone-opponent type of neurons are well modelled as a linear transformation of cone signals, L+M, L-M, and S-(L+M) with appropriate weights. In this framework, colours can be represented by a three-dimensional space consisting of three orthogonal axes, each of which exclusively represents signal of the L+M, L-M or S-(L+M) mechanism [1, 2].

Computer Vision and Image Understanding 107(1), 3–13 (2007) 22 A. Benoit et al. : Display Adaptive Tone Mapping. ACM Transactions on Graphics (Proc. : Perceptual Evaluation of Tone Mapping Operators with Real-World Sceness. J. ) Human Vision and Electronic Imaging X, IS&T/SPIE’s 17th Annual Symposium on Electronic Imaging, pp. 192–203. : A Perceptual Framework for Contrast Processing of High Dynamic Range Images (revised and extended version). : Enhancement of Bright Video Features for HDR Displays.

Our algorithm has linear complexity with respect to the number of image pixels and to the color quantization N . Therefore, it is particularly efficient, also in comparison to other methods, like for instance [3].

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Computational Color Imaging: Second International Workshop, CCIW 2009, Saint-Etienne, France, March 26-27, 2009. Revised Selected Papers by Hidehiko Komatsu, Naokazu Goda (auth.), Alain Trémeau, Raimondo Schettini, Shoji Tominaga (eds.)


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