By Alain Trémeau, Raimondo Schettini, Shoji Tominaga
ISBN-10: 331915978X
ISBN-13: 9783319159782
ISBN-10: 3319159798
ISBN-13: 9783319159799
This e-book constitutes the refereed complaints of the fifth Computational colour Imaging Workshop, CCIW 2015, held in Saint-Étienne, France, in March 2015. The 17 revised complete papers, awarded including five invited papers, have been rigorously reviewed and chosen from various submissions. The papers are geared up in topical sections on colour replica, colour sensation and belief, colour picture processing, spectral imaging, and colour in electronic cultural heritage.
Read Online or Download Computational Color Imaging: 5th International Workshop, CCIW 2015, Saint Etienne, France, March 24-26, 2015, Proceedings PDF
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Extra info for Computational Color Imaging: 5th International Workshop, CCIW 2015, Saint Etienne, France, March 24-26, 2015, Proceedings
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Examples of color name mappings based on calibrated data are the work of Mojsilovic [18] and Benavente et al. [1]. The latter proposed a parametric method to model color names. They introduce a fuzzy model which is fitted to data obtained from psychophysical experimental data. This data is well An Overview of Color Name Applications in Computer Vision 19 calibrated, meaning that the color samples are presented in a controlled laboratory environment under stable viewing conditions with known illuminant.
The interpolation technique is designed for the system in which the image set consists of RGB pixels with the spectral measurements and RGB pixels that do not have correspondence to the spectral data. It is expected to extend the interpolation method in future to the case when the pixel aperture sizes are different in RGB and spectral images, like the instances shown in figs. 2-4. 5 Experiments Performance of Different Reconstruction Methods In [21], the performance of the PW and ss-MAP estimation was compared and it was shown that the estimation accuracy was almost equivalent, while the computational cost in ss-MAP estimation was much higher.
Evaluation of linear models of surface spectral reflectance with small numbers of parameters. J. Opt. Soc. Am. A 3(10), 1673–1683 (1986) 29. : Spectral estimation techniques for the spectral calibration of a color image scanner. Appl. Opt. O. ro Abstract. This paper presents a unified approach for the relative pose estimation of a spectral camera - 3D Lidar pair without the use of any special calibration pattern or explicit point correspondence. The method works without specific setup and calibration targets, using only a pair of 2D-3D data.
Computational Color Imaging: 5th International Workshop, CCIW 2015, Saint Etienne, France, March 24-26, 2015, Proceedings by Alain Trémeau, Raimondo Schettini, Shoji Tominaga
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