The Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) imaging system aboard Terra platform consists of three subsystems: (1) Visible and near infrared (VNIR) operating in 3 bands with 15m spatial resolution; (2) Short wave infrared (SWIR) operating in 6 bands with 30m spatial resolution; and (3) Thermal infrared (TIR) operating in 5 bands with 90m spatial resolution. It is challenging to select band-ratios that can be displayed in the Red-Green-Blue (RGB) color combinations that give best results for extracting geological information from ASTER data. The Neoproterozoic Allaqi-Heiani suture in SE Egypt is used as a test site for the development of a methodology for the implementation of the optimum index factor (OIF) technique to rank all RGB color combinations using ASTER band-ratios. The 14 bands of ASTER data produce 182 band-ratios. These band-ratios allow for 988,260 RGB color combinations. All the 988,260 RGB combinations are ranked according to their OIF values in what is referred to as “blind” statistical processing. Blind statistics are then guided by a number of assumptions that are based on the spectral characteristics of the geological materials in the study area. (1) Excluding the TIR bands from the RGB color combinations since they measure emissivity whereas the VNIR and SWIR bands measure reflectivity. (2) When VNIR bands are used, the band-ratio is calculated by dividing the band with the longer wavelength by that which has a shorter wavelength. This is because the spectral curves of most geological materials have a positive slope in the VNIR portion of the electromagnetic spectrum. (3) When SWIR bands are used, the band-ratios are calculated by dividing the band with the shorter wavelength by that which has a longer wavelength. This is because spectral curves of most geological materials have slightly negative slopes in the SWIR portion of the electromagnetic spectrum. Our “filtered statistics” showed that ASTER images where band-ratios from the VNIR, SWIR and VNIR/SWIR are used in the RGB color combinations are effective in discriminating between different rock types.