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An Uncertainty-Aware Visual System for Image Pre-Processing
Article

Green Stability Assumption: Unsupervised Learning for Statistics-Based Illumination Estimation

Faculty of Electrical Engineering and Computing, University of Zagreb, Unska 3, HR-10000 Zagreb, Croatia
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J. Imaging 2018, 4(11), 127; https://doi.org/10.3390/jimaging4110127
Received: 31 August 2018 / Revised: 4 October 2018 / Accepted: 26 October 2018 / Published: 29 October 2018
(This article belongs to the Special Issue Image Enhancement, Modeling and Visualization)
In the image processing pipeline of almost every digital camera, there is a part for removing the influence of illumination on the colors of the image scene. Tuning the parameter values of an illumination estimation method for maximal accuracy requires calibrated images with known ground-truth illumination, but creating them for a given sensor is time-consuming. In this paper, the green stability assumption is proposed that can be used to fine-tune the values of some common illumination estimation methods by using only non-calibrated images. The obtained accuracy is practically the same as when training on calibrated images, but the whole process is much faster since calibration is not required and thus time is saved. The results are presented and discussed. The source code website is provided in Section Experimental Results. View Full-Text
Keywords: chromaticity; color constancy; gray-edge; gray-world; green; illumination estimation; shades-of-gray; standard deviation; unsupervised learning; white balancing chromaticity; color constancy; gray-edge; gray-world; green; illumination estimation; shades-of-gray; standard deviation; unsupervised learning; white balancing
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MDPI and ACS Style

Banić, N.; Lončarić, S. Green Stability Assumption: Unsupervised Learning for Statistics-Based Illumination Estimation. J. Imaging 2018, 4, 127. https://doi.org/10.3390/jimaging4110127

AMA Style

Banić N, Lončarić S. Green Stability Assumption: Unsupervised Learning for Statistics-Based Illumination Estimation. Journal of Imaging. 2018; 4(11):127. https://doi.org/10.3390/jimaging4110127

Chicago/Turabian Style

Banić, Nikola, and Sven Lončarić. 2018. "Green Stability Assumption: Unsupervised Learning for Statistics-Based Illumination Estimation" Journal of Imaging 4, no. 11: 127. https://doi.org/10.3390/jimaging4110127

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