Evaluating logarithmic kernel for spectral reflectance estimation—effects on model parametrization, training set size, and number of sensor spectral channels-Reference-Cited by-同舟云学术

Evaluating logarithmic kernel for spectral reflectance estimation—effects on model parametrization, training set size, and number of sensor spectral channels

Published:2014-02-13 Issue:3 Volume:31 Page:541
ISSN:1084-7529
Container-title:Journal of the Optical Society of America A
language:en
Short-container-title:J. Opt. Soc. Am. A

Author:

Eckhard Timo,Valero Eva M.,Hernández-Andrés Javier,Heikkinen Ville

Funder

Chromasens GmbH and University of Granada

Spanish Ministry of Research and innovation

Publisher

The Optical Society

Subject

Computer Vision and Pattern Recognition,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials

Reference5 articles.

1. Regularized learning framework in the estimation of reflectance spectra from camera responses

2. Evaluation and unification of some methods for estimating reflectance spectra from RGB images

3. Reflectance Estimation Using Local Regression Methods

4. Linear bases for representation of natural and artificial illuminants

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