Michael Moller

Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems

While variational methods have been among the most powerful tools for solving linear inverse problems in imaging, deep (convolutional) neural networks have recently taken the lead in many challenging benchmarks. A remaining drawback of deep learning approaches is their requirement for an expensive r…