ISETHDR: A Physics-based Synthetic Radiance Dataset for High Dynamic Range Driving Scenes
<|reference_start|>ISETHDR: A Physics-based Synthetic Radiance Dataset for High Dynamic Range Driving Scenes: This paper describes a physics-based end-to-end software simulation for image systems. We use the software to explore sensors designed to enhance performance in high dynamic range (HDR) environments, such as driving through daytime tunnels and under nighttime conditions. We synthesize physically realistic HDR spectral radiance images and use them as the input to digital twins that model the optics and sensors of different systems. This paper makes three main contributions: (a) We create a labeled (instance segmentation and depth), synthetic radiance dataset of HDR driving scenes. (b) We describe the development and validation of the end-to-end simulation framework. (c) We present a comparative analysis of two single-shot sensors designed for HDR. We open-source both the dataset and the software.<|reference_end|>
@article{liu2024isethdr:,
    title={ISETHDR: A Physics-based Synthetic Radiance Dataset for High Dynamic
  Range Driving Scenes},
    author={Zhenyi Liu, Devesh Shah, and Brian Wandell},
    journal={arXiv preprint arXiv:2408.12048},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.12048},
    primaryClass={cs.CV eess.IV}
}