Color correction target-based framework improvement exploiting the Euclidean color-difference formula for small-medium color differences in log-compressed OSA-UCS space

The solution to the problem of ‘color correction’ in digital photography is today very important to ensure a faithful reproduction of color in many fields as automotive, fashion, product design, interior design, art reproduction. Color correction techniques are today divided in the literature into two general categories: spectral sensitivity-based and color target-based approaches, as specified by ISO17321.14. The spectral sensitivity-based methods connect device-dependent and device-independent color spaces by a linear combination of camera spectral sensitivity curves and color matching functions. On the other hand, the target-based characterization methods establish the color relationship according to a set of color patches with available pre-measured spectral or colorimetric data. Despite their limits these latter achieved a growing success in the last years, essentially due to their flexibility and easy to use, and a rising improvement of research aimed at obtaining qualitative improvements. Basically, these investigations concerned two areas: A. Algorithm efficiency in the calculation of the transformation between measured CIE XYZ values and captured RGB values; B. Target types (i.e. tables with more patches, different color of patches, different material of the target patches). However, the number of researches aiming to improve the technique to measure the distance between CIE XYZ values and captured RGB values, allowing to find the transformation which minimize color error in the image reproduction are very limited. In this paper we focus on this problem, which we believe to be crucial to ensure an efficient color correction process. We experimented a new solution exploiting our color correction SHAFT [M.Gaiani, A.Ballabeni, SHAFT (SAT & HUE Adaptive Fine Tuning), a new automated solution for target-based color correction, in Colour and Colorimetry Multidisciplinay Contributions, AIC, 2018], an automated framework for target-based color correction that we benchmarked successfully in many and different use-cases. SHAFT exploits a set of optimization and enhancement techniques on exposure, contrast, white balance, hue and saturation for each RGB channel. The optimization process is guided by an iterative CIEDE2000 variation comparison. In this paper we present a variation of the framework replacing the CIEDE2000 with the Euclidean color-difference formula for small–medium color differences in log-compressed OSA-UCS space. Tests results of the new solution using a common reference, the target X-Rite ColorChecker Classic, and our dataset with images from many fields related to the CH and/or presenting typical problems of target-based CC algorithms, are presented showing that a lower number of iterations is required to reach the same numerical performance. Experiments with users are presented in order to evaluate the quality of the framework.