HistoHDR-Net: Histogram Equalization for Single LDR to HDR Image Translation

• URL: http://arxiv.org/abs/2402.06692v1
• Date: Thu, 8 Feb 2024 20:14:46 GMT
• Title: HistoHDR-Net: Histogram Equalization for Single LDR to HDR Image Translation
• Authors: Hrishav Bakul Barua, Ganesh Krishnasamy, KokSheik Wong, Abhinav Dhall, Kalin Stefanov
• Abstract summary: High Dynamic Range ( HDR) imaging aims to replicate the high visual quality and clarity of real-world scenes. 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. We propose a simple and effective method, Histo-Net, to recover the fine details.
• Score: 12.45632443397018
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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