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Spectral Adaptation Transform for Multispectral Constancy

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Abstract

The spectral reflectance of an object surface provides valuable information of its characteristics. Reflectance reconstruction from multispectral image data is typically based on certain assumptions. One of the common assumptions is that the same illumination is used for system calibration and image acquisition. The authors propose the concept of multispectral constancy which transforms the captured sensor data into an illuminant-independent representation, analogously to the concept of computational color constancy. They propose to transform the multispectral image data to a canonical representation through spectral adaptation transform (SAT). The performance of such a transform is tested on measured reflectance spectra and hyperspectral reflectance images. The authors also investigate the robustness of the transform to the inaccuracy of illuminant estimation in natural scenes. Results of reflectance reconstruction show that the proposed SAT is efficient and is robust to error in illuminant estimation.
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Document Type: Research Article

Publication date: 01 March 2018

This article was made available online on 27 March 2018 as a Fast Track article with title: "Spectral Adaptation Transform for Multispectral Constancy".

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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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    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 paper for details.

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