Robust Multi-Image HDR Reconstruction for the Modulo Camera
This work addresses noise robustness in HDR reconstruction for consumer cameras using modulo sensors, offering an incremental improvement over prior methods.
The paper tackles the problem of reconstructing high dynamic range (HDR) images from multiple exposures using a modulo camera, which captures fewer images than conventional sensors but is sensitive to noise, and proposes a robust algorithm that reduces artifacts and outperforms the baseline on real data.
Photographing scenes with high dynamic range (HDR) poses great challenges to consumer cameras with their limited sensor bit depth. To address this, Zhao et al. recently proposed a novel sensor concept - the modulo camera - which captures the least significant bits of the recorded scene instead of going into saturation. Similar to conventional pipelines, HDR images can be reconstructed from multiple exposures, but significantly fewer images are needed than with a typical saturating sensor. While the concept is appealing, we show that the original reconstruction approach assumes noise-free measurements and quickly breaks down otherwise. To address this, we propose a novel reconstruction algorithm that is robust to image noise and produces significantly fewer artifacts. We theoretically analyze correctness as well as limitations, and show that our approach significantly outperforms the baseline on real data.