Single-Photon Camera Guided Extreme Dynamic Range Imaging

Yuhao Liu, Felipe Gutierrez-Barragan, Atul Ingle, Mohit Gupta, Andreas Velten; Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2022, pp. 1575-1585


Reconstruction of high-resolution extreme dynamic range images from a small number of low dynamic range (LDR) images is crucial for many computer vision applications. Current high dynamic range (HDR) cameras based on CMOS image sensor technology rely on multiexposure bracketing which suffers from motion artifacts and signal-to-noise (SNR) dip artifacts in extreme dynamic range scenes. Recently, single-photon cameras (SPCs) have been shown to achieve orders of magnitude higher dynamic range for passive imaging than conventional CMOS sensors. SPCs are becoming increasingly available commercially, even in some consumer devices. Unfortunately, current SPCs suffer from low spatial resolution. To overcome the limitations of CMOS and SPC sensors, we propose a learning-based CMOS-SPC fusion method to recover high-resolution extreme dynamic range images. We compare the performance of our method against various traditional and state-of-the-art baselines using both synthetic and experimental data. Our method outperforms these baselines, both in terms of visual quality and quantitative metrics.

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@InProceedings{Liu_2022_WACV, author = {Liu, Yuhao and Gutierrez-Barragan, Felipe and Ingle, Atul and Gupta, Mohit and Velten, Andreas}, title = {Single-Photon Camera Guided Extreme Dynamic Range Imaging}, booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)}, month = {January}, year = {2022}, pages = {1575-1585} }