Dual-Camera Joint Deblurring-Denoising
Shayan Shekarforoush Amanpreet Walia Marcus A. Brubaker Konstantinos G. Derpanis Alex Levinshtein
Recent image enhancement methods have shown the advantages of using a pair of
long and short-exposure images for low-light photography. These image
modalities offer complementary strengths and weaknesses. The former yields an
image that is clean but blurry due to camera or object motion, whereas the
latter is sharp but noisy due to low photon count. Motivated by the fact that
modern smartphones come equipped with multiple rear-facing camera sensors, we
propose a novel dual-camera method for obtaining a high-quality image. Our
method uses a synchronized burst of short exposure images captured by one
camera and a long exposure image simultaneously captured by another. Having a
synchronized short exposure burst alongside the long exposure image enables us
to (i) obtain better denoising by using a burst instead of a single image, (ii)
recover motion from the burst and use it for motion-aware deblurring of the
long exposure image, and (iii) fuse the two results to further enhance quality.
Our method is able to achieve state-of-the-art results on synthetic dual-camera
images from the GoPro dataset with five times fewer training parameters
compared to the next best method. We also show that our method qualitatively
outperforms competing approaches on real synchronized dual-camera captures.