Welcome to the Computational Imaging Group (CIG)!
Computational Imaging is a rapidly growing research area at the intersection of image processing, computer vision, physical sciences, and machine learning. Computational Imaging Group (CIG) at Washington University researches new methods for reliable acquisition, efficient processing, and automated analysis of spatiotemporal data. Application include biomedical imaging, material sciences, geospatial intelligence, space exploration, industrial inspection, and consumer electronics. We develop algorithms and theoretical foundations for enabling advanced capabilities in future imaging systems. We have expertise in large-scale optimization, signal and image processing, machine learning, computer vision, and statistical inference. Our research is inherently interdisciplinary and includes collaborations with researchers in optics, medicine, physics, and biology.
September 2019: Infusing Learned Priors into Model-Based Multispectral Imaging was accepted to IEEE CAMSAP 2019.
September 2019: Online Regularization by Denoising with Applications to Phase Retrieval will be presented at ICCV 2019 workshop on Learning for Computational Imaging.