ORGB: Offset Correction in RGB Color Space for Illumination-Robust Image Processing

TL;DR

This paper introduces ORGB, a method for correcting illumination-induced offsets in RGB space, enhancing robustness in image processing tasks like road detection by making color representations less affected by shadows.

Contribution

It presents a novel offset correction technique in RGB space based on an optical model, improving illumination robustness without altering image appearance.

Findings

Improved road detection performance with ORGB images.

Effective offset detection and removal method.

Enhanced shadow robustness in image processing.

Abstract

Single materials have colors which form straight lines in RGB space. However, in severe shadow cases, those lines do not intersect the origin, which is inconsistent with the description of most literature. This paper is concerned with the detection and correction of the offset between the intersection and origin. First, we analyze the reason for forming that offset via an optical imaging model. Second, we present a simple and effective way to detect and remove the offset. The resulting images, named ORGB, have almost the same appearance as the original RGB images while are more illumination-robust for color space conversion. Besides, image processing using ORGB instead of RGB is free from the interference of shadows. Finally, the proposed offset correction method is applied to road detection task, improving the performance both in quantitative and qualitative evaluations.