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21 December 1999 Illumination estimation using linear decomposition and constrained optimization
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Abstract
We investigate the problem of estimating scene illumination from an image. By approximating the spectral surface reflectance and the illumination spectra power distribution in finite linear spaces, the projection of the illumination onto the linear space is computed by minimizing the error in pixel value. The solution space is constrained by using the physical properties of both reflectance and illumination. Various techniques such as multiple hypotheses (hence multiple linear spaces) for illumination are used to improve the results. We have found that by approximating the surface reflectance in a 3 or 4 dimensional linear space and the illumination in a 5 or 6 dimensional linear space, the new algorithm significantly outperforms the gray-world algorithm for RGB images.
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Bo Tao and Ingeborg Tastl "Illumination estimation using linear decomposition and constrained optimization", Proc. SPIE 3963, Color Imaging: Device-Independent Color, Color Hardcopy, and Graphic Arts V, (21 December 1999); https://doi.org/10.1117/12.373393
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