301 citations · 1.4k across the 51 of their papers we have counts for
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Plug-In Stochastic Gradient Method
Yu Sun, Brendt Wohlberg, Ulugbek S. Kamilov
Plug-and-play priors (PnP) is a popular framework for regularized signal reconstruction by using advanced denoisers within an iterative algorithm. In this paper, we discuss our rec…
Regularized Fourier Ptychography using an Online Plug-and-Play Algorithm
Yu Sun, Shiqi Xu, Yunzhe Li +3
The plug-and-play priors (PnP) framework has been recently shown to achieve state-of-the-art results in regularized image reconstruction by leveraging a sophisticated denoiser with…
Learning Multi-Layer Transform Models
Saiprasad Ravishankar, Brendt Wohlberg
Learned data models based on sparsity are widely used in signal processing and imaging applications. A variety of methods for learning synthesis dictionaries, sparsifying transform…
Convolutional Dictionary Regularizers for Tomographic Inversion
Singanallur Venkatakrishnan, Brendt Wohlberg
There has been a growing interest in the use of data-driven regularizers to solve inverse problems associated with computational imaging systems. The convolutional sparse represent…
An Online Plug-and-Play Algorithm for Regularized Image Reconstruction
Yu Sun, Brendt Wohlberg, Ulugbek S. Kamilov
Plug-and-play priors (PnP) is a powerful framework for regularizing imaging inverse problems by using advanced denoisers within an iterative algorithm. Recent experimental evidence…
Efficient Projection onto the Mixed-Norm Ball using a Newton root search method
Gustavo Chau, Brendt Wohlberg, Paul Rodriguez
Mixed norms that promote structured sparsity have numerous applications in signal processing and machine learning problems. In this work, we present a new algorithm, based on a New…