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Spectral recovery of artificial illuminants using a CCD colour camera with Non-negative Matrix Factorization and Independent Component Analysis

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We investigated the quality of the spectral estimation of incandescent and fluorescent illuminants using Non-negative Matrix Factorization (NMF), Independent Component Analysis (ICA) and a direct pseudo-inverse approach. We simulated the response of a commercial digital CCD camera coupled or not with coloured filters to a set of natural and artificial illuminants. None of the recovery algorithms used here needed information about spectral sensitivities of the camera sensors or eigenvectors to estimate the spectral power distributions of illuminants. Although nonnegative algorithms can reduce the computational cost of spectral devices, experiments show that ICA and direct pseudo-inverse methods consistently outperforms the NMF approaches, even for fluorescent lights and even using a reduced training set of illuminants.
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Document Type: Research Article

Publication date: January 1, 2006

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  • Started in 2002 and merged with the Color and Imaging Conference (CIC) in 2014, CGIV covered a wide range of topics related to colour and visual information, including color science, computational color, color in computer graphics, color reproduction, volor vision/psychophysics, color image quality, color image processing, and multispectral color science. Drawing papers from researchers, scientists, and engineers worldwide, DGIV offered attendees a unique experience to share with colleagues in industry and academic, and on national and international standards committees. Held every year in Europe, DGIV papers were more academic in their focus and had high student participation rates.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual papers for details.

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