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Spectral Estimation of Multiple Light Sources based on Highlight Detection

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The authors discuss the spectral estimation of multiple light sources from image data in a complex illumination environment. An approach is proposed to effectively estimate illuminant spectra and the corresponding light sources based on highlight areas that appear on dielectric object surfaces. First, the authors develop a highlight detection method using two types of convolution filters with Gaussian distributions, center-surround and low-pass filters. This method is available even for white surfaces, and it is independent of object color and of viewing and incidence angles. Second, they present an algorithm for estimating the illuminant spectra from extracted highlight areas. Each specular highlight area has a spectral composition corresponding to only one light source among multiple light sources. The spectral image data are projected onto a two-dimensional subspace, where a linear cluster in pixel distribution is detected for each highlight area. Third, the relative positional relationship between highlight areas among different object surfaces is used to identify the light sources on each surface. The authors develop an algorithm based on probabilistic relaxation labeling. The light source for each highlight and the corresponding spectral-power distribution are determined from the iterative labeling process. Finally, the feasibility of the proposed approach is examined in an experiment using a real complex environment, where dielectric objects are illuminated by multiple light sources of light-emitting diode, fluorescence, and incandescence.
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Document Type: Research Article

Affiliations: 1: Department of Computer Science, Norwegian University of Science and Technology, 2815 Gjøvik, Norway 2: Department of Imaging Sciences, Chiba University, Chiba 263-8522, Japan

Publication date: September 1, 2020

This article was made available online on September 4, 2020 as a Fast Track article with title: "Spectral Estimation of Multiple Light Sources based on Highlight Detection".

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  • The Journal of Imaging Science and Technology (JIST) is dedicated to the advancement of imaging science knowledge, the practical applications of such knowledge, and how imaging science relates to other fields of study. The pages of this journal are open to reports of new theoretical or experimental results, and to comprehensive reviews. Only original manuscripts that have not been previously published, nor currently submitted for publication elsewhere, should be submitted.

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