To reproduce colors in one system which differs from another system in terms of the color gamut, it is necessary to use a color gamut mapping process. This color gamut mapping is a method to translate a specific color from a medium (screen, digital camera, scanner, digital file, etc) into another system having a difference in gamut volume. There are different rendering intent options defined by the International Color Consortium  to use the different reproduction goals of the user . Any rendering intent used to reproduce colors, includes profile engine decisions to do it, i.e. looking for color accuracy, vivid colors or pleasing reproduction of images. Using the same decisions on different profile engines, the final visual output can look different (more than one Just Noticeable Difference) depending on the profile engine used and the color algorithms that they implement. Profile performance substantially depends on the profiler engine used to create them. Different profilers provide the user with varying levels of liberty to design a profile for their color management needs and preference. The motivation of this study is to rank the performance of various market leading profiler engines on the basis of different metrics designed specifically to report the performance of particular aspects of these profiles. The study helped us take valuable decisions regarding profile performance without any visual assessment to decide on the best profiler engine.
Pooshpanjan Roy Biswas, Alessandro Beltrami, Joan Saez Gomez, "A testing paradigm for quantifying ICC profilers" in Proc. IS&T 27th Color and Imaging Conf., 2019, pp 80 - 85, https://doi.org/10.2352/issn.2169-2629.2019.27.15