189 citations · 311 across the 19 of their papers we have counts for
6 papers · 1 filter
Snapshot High Dynamic Range Imaging with a Polarization Camera
Mingyang Xie, Matthew Chan, Christopher Metzler
High dynamic range (HDR) images are important for a range of tasks, from navigation to consumer photography. Accordingly, a host of specialized HDR sensors have been developed, the…
Denoising Generalized Expectation-Consistent Approximation for MR Image Recovery
Saurav K. Shastri, Rizwan Ahmad, Christopher A. Metzler +1
To solve inverse problems, plug-and-play (PnP) methods replace the proximal step in a convex optimization algorithm with a call to an application-specific denoiser, often implement…
Supervision by Denoising for Medical Image Segmentation
Sean I. Young, Adrian V. Dalca, Enzo Ferrante +4
Learning-based image reconstruction models, such as those based on the U-Net, require a large set of labeled images if good generalization is to be guaranteed. In some imaging doma…
SUREMap: Predicting Uncertainty in CNN-based Image Reconstruction Using Stein's Unbiased Risk Estimate
Ruangrawee Kitichotkul, Christopher A. Metzler, Frank Ong +1
Convolutional neural networks (CNN) have emerged as a powerful tool for solving computational imaging reconstruction problems. However, CNNs are generally difficult-to-understand b…
Deep Learning Techniques for Inverse Problems in Imaging
Gregory Ongie, Ajil Jalal, Christopher A. Metzler +3
Recent work in machine learning shows that deep neural networks can be used to solve a wide variety of inverse problems arising in computational imaging. We explore the central pre…
Deep Optics for Single-shot High-dynamic-range Imaging
Christopher A. Metzler, Hayato Ikoma, Yifan Peng +1
High-dynamic-range (HDR) imaging is crucial for many computer graphics and vision applications. Yet, acquiring HDR images with a single shot remains a challenging problem. Whereas…