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Assessment of Affine Transforms for illumination compensation of colour images using a Mixtures of Gaussians model

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In this paper we present a method to obtain the parameters of a general affine transform for illumination compensation of two data sets, modelling one of them using a Mixture of Gaussians (MoGs), and applying an iterative strategy for the other group of data, obtaining the parameters of the transform using a Maximum-Likelihood criterion in a first step, and updating the a posteriori membership probabilities for the other group of data, in the second step. With this approach it is not necessary that the two data sets have a perfect pixel-wise correspondence, and more complex compensations like including change in acquisition setup can be considered.
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Document Type: Research Article

Publication date: January 1, 2008

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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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