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Open Access Multiple Illuminants’ Color Estimation using Layered Gray-World Assumption

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Illuminant color estimation in an image under multiple illuminations is proposed. In the most conventional methods, the image is divided into small regions and estimated the local illuminant in each region by applying the methods for one illuminant. By unifying the derived local illuminants, scene illuminants are estimated. The methods for one illuminant used in the conventional ones are typically gray-world, white-patch, first-order and second-order gray-edge, and so on. However, these methods are not modified properly. Therefore, they have possibilities for improving in illuminant color estimation. Proposed method is gray-world based and applies to each small region to estimate the local illuminant. There are two features in the methods. The first feature is the selection of the small regions; the method uses criteria for the regions whether they satisfy the gray-world assumption and estimates the local illuminants in the selected small ones. The second one is the use of multi-layered small regions; in general, appropriate size of the small region depends on the image, thus, several-sized small regions corresponding to the resolution are used and unified. Experiment results using Mondrian pattern images under the reddish and white illuminants show that the estimation error by the proposed method is relatively smaller than that by the conventional one.
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Keywords: color constancy; gray world assumption; illuminant color estimation

Document Type: Research Article

Publication date: January 13, 2019

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