ORGB: Offset Correction in RGB Color Space for Illumination-Robust Image Processing
This addresses illumination robustness in image processing for applications like road detection, but it is incremental as it builds on existing color space theories.
The paper tackled the problem of color lines in RGB space not intersecting the origin under severe shadows, which affects illumination robustness, by proposing an offset correction method called ORGB, resulting in improved road detection performance with quantitative and qualitative gains.
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.