HistoHDR-Net: Histogram Equalization for Single LDR to HDR Image Translation
<|reference_start|>HistoHDR-Net: Histogram Equalization for Single LDR to HDR Image Translation: High Dynamic Range (HDR) imaging aims to replicate the high visual quality and clarity of real-world scenes. Due to the high costs associated with HDR imaging, the literature offers various data-driven methods for HDR image reconstruction from Low Dynamic Range (LDR) counterparts. A common limitation of these approaches is missing details in regions of the reconstructed HDR images, which are over- or under-exposed in the input LDR images. To this end, we propose a simple and effective method, HistoHDR-Net, to recover the fine details (e.g., color, contrast, saturation, and brightness) of HDR images via a fusion-based approach utilizing histogram-equalized LDR images along with self-attention guidance. Our experiments demonstrate the efficacy of the proposed approach over the state-of-art methods.<|reference_end|>
@article{barua2024histohdr-net:,
    title={HistoHDR-Net: Histogram Equalization for Single LDR to HDR Image
  Translation},
    author={Hrishav Bakul Barua, Ganesh Krishnasamy, KokSheik Wong, Abhinav Dhall,
  Kalin Stefanov},
    journal={arXiv preprint arXiv:2402.06692},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.06692},
    primaryClass={eess.IV cs.AI cs.CV cs.GR cs.LG cs.MM}
}