Within the context of Digital Image Correlation (DIC), the optimal treatment of color images is considered. The mathematical bases of a weighted 3-field image correlation are first introduced , which are relevant for RGB encoded images. In this framework, noise characterization methods are developed as noise properties dictate the best suited metric to compare images. Consistent ways to process an image from elementary Bayer matrices are derived. Last, a case study on uncertainty quantification is performed.