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

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.