Multi-Bracket High Dynamic Range Imaging with Event Cameras
This addresses the problem of HDR imaging in dynamic scenes for computer vision applications, representing an incremental advancement by integrating event cameras into existing pipelines.
The paper tackles the challenge of high dynamic range (HDR) imaging in dynamic scenes by proposing a multi-bracket pipeline that combines a standard camera with an event camera, resulting in improved robustness with PSNR gains of up to 5dB on synthetic data and 0.7dB on real-world data.
Modern high dynamic range (HDR) imaging pipelines align and fuse multiple low dynamic range (LDR) images captured at different exposure times. While these methods work well in static scenes, dynamic scenes remain a challenge since the LDR images still suffer from saturation and noise. In such scenarios, event cameras would be a valid complement, thanks to their higher temporal resolution and dynamic range. In this paper, we propose the first multi-bracket HDR pipeline combining a standard camera with an event camera. Our results show better overall robustness when using events, with improvements in PSNR by up to 5dB on synthetic data and up to 0.7dB on real-world data. We also introduce a new dataset containing bracketed LDR images with aligned events and HDR ground truth.