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An Online Plug-and-Play Algorithm for Regularized Image Reconstruction
TLDR
In this paper, we introduce a new online PnP algorithm based on the proximal gradient method (PGM). Expand
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Message-Passing De-Quantization With Applications to Compressed Sensing
TLDR
This paper develops message-passing de-quantization algorithms for minimum mean-squared error estimation of a random vector from quantized linear measurements, notably allowing the linear expansion to be overcomplete or undercomplete and the scalar quantization to be regular or non-regular. Expand
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Learning Optimal Nonlinearities for Iterative Thresholding Algorithms
TLDR
We present a data-driven scheme for learning optimal thresholding functions for ISTA. Expand
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Optical Tomographic Image Reconstruction Based on Beam Propagation and Sparse Regularization
TLDR
We present a novel iterative imaging method for optical tomography that combines a nonlinear forward model based on the beam propagation method (BPM) with an edge-preserving three-dimensional (3-D) total variation (TV) regularizer. Expand
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Image Restoration Using Total Variation Regularized Deep Image Prior
TLDR
This paper extends the DIP framework by combining it with the traditional TV regularization. Expand
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Approximate Message Passing With Consistent Parameter Estimation and Applications to Sparse Learning
TLDR
We consider the estimation of an independent and identically distributed (i.i.d.) (possibly non-Gaussian) vector x ∈ Rm obtained by a general cascade model consisting of a known linear transform followed by a probabilistic componentwise measurement channel. Expand
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One-Bit Measurements With Adaptive Thresholds
TLDR
We introduce a new method for adaptive one-bit quantization of linear measurements and propose an algorithm for the recovery of signals based on generalized approximate message passing (GAMP). Expand
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Compressive imaging with iterative forward models
TLDR
We propose a new compressive imaging method for reconstructing 2D or 3D objects from their scattered wave-field measurements. Expand
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Online convolutional dictionary learning for multimodal imaging
TLDR
We propose a new method that reconstructs multimodal images from their linear measurements by exploiting redundancies across different modalities. Expand
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Regularized Fourier Ptychography Using an Online Plug-and-play Algorithm
TLDR
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 within an iterative algorithm. Expand
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