DeepDuoHDR: A Low Complexity Two Exposure Algorithm for HDR Deghosting on Mobile Devices

被引：0
|
作者：
Alpay, Kadir Cenk [1 ]
Akyüz, Ahmet Oǧuz [1 ]
Brandonisio, Nicola [2 ]
Meehan, Joseph [2 ]
Chalmers, Alan [3 ]
机构：
[1] Middle East Technical University, Department of Computer Engineering, Ankara,06800, Turkey
[2] Huawei Technologies, Mougins,06250, France
[3] University of Warwick, Wmg, Coventry,CV4 7AL, United Kingdom
来源：
IEEE Transactions on Image Processing | 2024年 / 33卷
关键词：
The increased interest in consumer-grade high dynamic range (HDR) images and videos in recent years has caused a proliferation of HDR deghosting algorithms. Despite numerous proposals; a fast; memory-efficient; and robust algorithm has been difficult to achieve. This paper addresses this problem by leveraging the power of attention and U-Net-based neural representations and using a conservative deghosting strategy. Given two bracketed exposures of a scene; we produce an HDR image that maximally resembles the high exposure where it is well-exposed and fuses aligned information from both exposures otherwise. We evaluate the performance of our algorithm under several different challenging scenarios; using both visual and quantitative results; and show that it matches the state-of-the-art algorithms despite using only two exposures and having significantly lower computational complexity. Furthermore; the parameters of our algorithm greatly simplify deploying its different versions for devices with a variety of computational constraints; including mobile devices. © 1992-2012 IEEE;
D O I：
10.1109/TIP.2024.3497838
中图分类号：
学科分类号：
摘要：
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页码：6592 / 6606
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