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：

引用

页码：6592 / 6606

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