Authors:
Furkan Kınlı
1
;
Barış Özcan
2
and
Furkan Kıraç
1
Affiliations:
1
Department of Computer Science, Özyeğin University, İstanbul, Turkey
;
2
Department of Computer Engineering, Bahçeşehir University, İstanbul, Turkey
Keyword(s):
High Dynamic Range, Image Statistics, Low-Light Imaging, Naka-Rushton Equation, Tone Mapping Operator, Retinex.
Abstract:
We introduce Dawn, a novel Tone Mapping Operator (TMO) designed to address the limitations of state-of-the-art TMOs such as Flash and Storm, particularly in challenging lighting conditions. While existing methods perform well in stable, well-lit, single-illuminant environments, they struggle with multi-illuminant and low-light scenarios, often leading to artifacts, amplified noise, and color shifts due to the additional step to adjust overall scene brightness. Dawn solves these issues by adaptively inferring the scaling parameter for the Naka-Rushton Equation through a weighted combination of luminance mean and variance. This dynamic approach allows Dawn to handle varying illuminant conditions, reducing artifacts and improving image quality without requiring additional adjustments to scene brightness. Our experiments show that Dawn matches the performance of current state-of-the-art TMOs on HDR datasets and outperforms them in low-light conditions, providing superior visual results.
The source code for Dawn will be available at https://github.com/birdortyedi/ dawn-tmo/.
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