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J. Imaging 2017, 3(3), 35;

Color Consistency and Local Contrast Enhancement for a Mobile Image-Based Change Detection System

Advanced Visionics and Processing Group, French-German Research Institute of Saint-Louis, 5 rue du Général Cassagnou, 68300 Saint-Louis, France
Author to whom correspondence should be addressed.
Received: 30 June 2017 / Revised: 31 July 2017 / Accepted: 8 August 2017 / Published: 23 August 2017
(This article belongs to the Special Issue Color Image Processing)
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Mobile change detection systems allow for acquiring image sequences on a route of interest at different time points and display changes on a monitor. For the display of color images, a processing approach is required to enhance details, to reduce lightness/color inconsistencies along each image sequence as well as between corresponding image sequences due to the different illumination conditions, and to determine colors with natural appearance. We have developed a real-time local/global color processing approach for local contrast enhancement and lightness/color consistency, which processes images of the different sequences independently. Our approach combines the center/surround Retinex model and the Gray World hypothesis using a nonlinear color processing function. We propose an extended gain/offset scheme for Retinex to reduce the halo effect on shadow boundaries, and we employ stacked integral images (SII) for efficient Gaussian convolution. By applying the gain/offset function before the color processing function, we avoid color inversion issues, compared to the original scheme. Our combined Retinex/Gray World approach has been successfully applied to pairs of image sequences acquired on outdoor routes for change detection, and an experimental comparison with previous Retinex-based approaches has been carried out. View Full-Text
Keywords: color consistency; local contrast enhancement; Retinex; change detection color consistency; local contrast enhancement; Retinex; change detection

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Tektonidis, M.; Monnin, D. Color Consistency and Local Contrast Enhancement for a Mobile Image-Based Change Detection System. J. Imaging 2017, 3, 35.

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