Russell Finn, Midgley William J B
School of Mechanical and Manufacturing Engineering, UNSW Sydney, Sydney, NSW 2052, Australia.
Sensors (Basel). 2024 Sep 10;24(18):5876. doi: 10.3390/s24185876.
Stereo high dynamic range imaging (SHDRI) offers a more temporally stable solution to high dynamic range (HDR) imaging from low dynamic range input images compared to bracketing and removes the loss of accuracy that single-image HDR solutions offer. However, few solutions currently exist that take advantage of the different (asymmetric) lenses, commonly found on modern smartphones, to achieve SHDRI. This paper presents a method that achieves single-shot asymmetric HDR fusion via a reference-based deep learning approach. Results demonstrate a system that is more robust to aperture and image signal processing pipeline differences than existing solutions.
与包围曝光相比，立体高动态范围成像（SHDRI）能从低动态范围输入图像中为高动态范围（HDR）成像提供更具时间稳定性的解决方案，并消除了单图像HDR解决方案所带来的精度损失。然而，目前很少有解决方案利用现代智能手机上常见的不同（非对称）镜头来实现SHDRI。本文提出了一种通过基于参考的深度学习方法实现单次非对称HDR融合的方法。结果表明，该系统比现有解决方案对光圈和图像信号处理管道差异具有更强的鲁棒性。
