Gain-Pixel Visualization Algorithm Designed for Computational Color Constancy Scheme

Abstract

Color constancy (CC) is an essential part of machine vision. Previously reported CC algorithms lacked consistent and clear-cut evaluation diagrams. This paper instead presents a gain-pixel visualization CC algorithm which uses optimization numerical analysis and 2D-3D graphical displays. This graph-based CC algorithm differs from others in that it gives a clear overall perspective on finding the appropriate amount of RGB gain adjustment to achieve image CC. The ground truth (GT) image, which is critical for data accuracy, has been used as a benchmark or a target in image CC. However, GT images in CC are often inconsistently determined or manually checked. This paper will illustrate that an accurate and specific GT image can be obtained or checked using an optimization scheme, namely the grayscale pixel maximization (GPM). Using previously published image CC results for evaluation and comparison, this paper demonstrates the usefulness, accuracy, and especially the forensic capability of this CC algorithm.