There are many different Retinex algorithms. They make different assumptions, and attempt to solve different problems. They have different goals, ground truths and output results. This "Retinex at 50 Workshop" session compares the variety of Retinex algorithms, along with their goals, ground truths that measure the success of their results. All Retinex algorithms use spatial comparisons to calculate the appearances of the entire scene. All Retinex algorithms need observer data to quantify human vision, so as to evaluate their accuracy. The most critical component of all Retinex experiments is the observer matches used to characterize human spatial vision. This paper reviews the experiments that have evolved as a result of Retinex Theory. They provide a very challenging data set for algorithms that predict appearance.
John J McCann, "Retinex Algorithms: Many spatial processes used to solve many different problems" in Proc. IS&T Int’l. Symp. on Electronic Imaging: Retinex at 50, 2016, https://doi.org/10.2352/ISSN.2470-1173.2016.6.RETINEX-017