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There are various color correction techniques that can be applied to digital photographs to account for environmental lighting variations. This manuscript contains a proposed method for such color correction. The method involves saturating an image by a specified percentage of its pixels via upper and lower percentage histogram manipulation using the image’s RGB histograms. Variations of this new technique, the white balance (WB) correction method, and a multivariable fit are used to test its performance against common color correction techniques. The findings demonstrate that the upper and lower percentage histogram manipulation method is not only more applicable to photos because it doesn’t require calibration regions to be sampled but it is also more consistent in its correction of photos when there are substantial gray scale features (e.g. a black and white grid or text). Our motivation for testing these techniques is to find the most robust color correction technique that is broadly applicable (not requiring a color checker chart) and is consistent across different lighting. KEYWORDS: Color Correction; Histogram Manipulation; Saturation; White Balance; Scientific Image Analysis; Color Comparisons; Euclidean Distance; Standard Deviation; Color Difference