ProLab: A Perceptually Uniform Projective Color Coordinate System

Ivan A Konovalenko,Anna A Smagina,Petr P Nikolaev,Dmitry P Nikolaev

doi:10.1109/access.2021.3115425

Abstract

The construction of perceptually uniform color space is an important task of color theory. Many image processing applications requires the color difference to replicate human perception. The perceptual difference is poorly approximated by Euclidean distance within linear color coordinate systems, in particular, within CIE XYZ. Almost all uniform color spaces are constructed as some nonlinear transformation from CIE XYZ. Such transformations do not preserve the straightness of the color tone curves and other collinearity properties which are important for high dynamic range and wide color gamut imagery and required for linear color analysis, including separation of homogeneous backgrounds. In this work, we propose proLab, a new color coordinate system derived as a 3D projective transformation of CIE XYZ that preserves the linearity of manifolds by definition. We show that proLab is far superior to the widely used CIELAB coordinate system (though inferior to the modern CAM16-UCS) in terms of perceptual uniformity, evaluated by the STRESS metric in reference to the CIEDE2000 color difference formula. We also demonstrate that shot noise in proLab is more homoscedastic than in CAM16-UCS or other standard color spaces. This makes proLab a convenient coordinate system for linear color analysis.

Highlights

The purpose of this work is to develop a new color coordinate system for the analysis of color images of the visible light spectrum
Most existing algorithms for color analysis operate with distances in a color space, and some of them rely on the linear properties of color distributions
ProLab is a novel color coordinate system that is demonstrated to be superior to CIELAB in perceptual uniformity while still preserving color manifold linearity

Summary

Introduction

The purpose of this work is to develop a new color coordinate system for the analysis of color images of the visible light spectrum. Most existing algorithms for color analysis operate with distances in a color space, and some of them rely on the linear properties of color distributions. The color space metric, as a rule, is not derived strictly from physical models but rather from the properties of human color perception using psychophysiological experimental data. The color coordinate system proposed in this work is based on the color perception model as well as on physical models of image formation; for an accurate problem statement, we have to provide a detailed introduction.

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Conclusion