Paper
15 June 2023 RGB and IR imagery fusion for autonomous driving
Author Affiliations +
Abstract
Compressed sensing theory allows for a high-resolution image recovery of sparse image data. However, image scene data from an RGB camera, captured at night-time or in fog, dust, or rainy conditions, is difficult to read. The fusion of IR camera data with RGB camera data allows us to determine the difference between objects in the scene and noise (dust, rain, fog). This paper demonstrates a compressive sensing methodology applied to the scattered image data of the RGB camera to determine objects or obstacles in a scene, which allows for low-cost solutions for the problem of autonomous driving in unfair imaging conditions.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shravan Kumar Swamy, Klaus Schwarz, Michael Hartmann, and Reiner Creutzburg "RGB and IR imagery fusion for autonomous driving", Proc. SPIE 12526, Multimodal Image Exploitation and Learning 2023 , 125260Q (15 June 2023); https://doi.org/10.1117/12.2664336
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image fusion

Object detection

Infrared imaging

RGB color model

Image quality

Infrared sensors

Autonomous driving

Back to Top