Hybrid model of alternating least squares and root polynomial technique for color correction

Color correction is an image-altering technique that modifies image color in such a way it matches reference image. Many approaches have already been proposed by various researchers; however, those models unable to reduce errors between two images, which results inefficiency and poor-quality images. This research paper presents effective improved model wherein alternate least square (ALS) root polynomial (RP) are used together. The main objective of the error target enhance quality make them look realistic. To achieve this objective, Amsterdam library object images contains picture single objects captured under illumination angles colors. contribution hybrid ALS + RP technique, implemented on dataset fixes its as per enhances quality. then converted into three models, i.e., LAB, LUV, RGB XYZ format. Finally, difference observed calculating values for parameters like Mean, median, 95% quantile, maximum error. effectiveness suggested approach assessed validated MATLAB software each model. Through extensive experiments, yields followed up LUV prove supremacy over other models.