Low-light image enhancement based on simulated multi-exposure fusion

We propose an efficient and novel framework for low-light image enhancement, which aims to reveal information hidden in the darkness and improve overall brightness and local contrast. Inspired by exposure fusion technique, we employ simulated multi-exposure images fusion to derive bright, natural an...

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Bibliographic Details
Published in:Journal of physics. Conference series 2023-06, Vol.2478 (6), p.62022
Main Authors: Han, Yongcheng, Zhang, Wenwen, He, Weiji
Format: Article
Language:English
Subjects:
Darkness
Exposure
Image contrast
Image enhancement
Modules
Physics
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Summary:We propose an efficient and novel framework for low-light image enhancement, which aims to reveal information hidden in the darkness and improve overall brightness and local contrast. Inspired by exposure fusion technique, we employ simulated multi-exposure images fusion to derive bright, natural and satisfactory results, while images are taken under poor conditions such as insufficient or uneven illumination, back-lit and limited exposure time. Specifically, we first design a novel method to generate synthesized images with varying exposure time from a single image. Thus, each image of these artificial sequences contains necessary information for the final desired enhanced result. We then introduce a flexible multi-exposure fusion framework to achieve fused images, which comprises a weight map prediction module and a multi-scale fusion module. Extensive experiments show that our approach can achieve similar or better performance compared to serval state-of-the-art methods.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2478/6/062022