A denoising algorithm seeks to remove noise, errors, or perturbations from a signal. Extensive research has been devoted to this arena over the last several decades, and as a result, today's denoisers can effectively remove large amounts of additive white Gaussian noise. A compressed sensing (CS) reconstruction algorit…
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3 results for “D-AMP”
New neural network LDAMP outperforms existing algorithms in image recovery.
problem Challenging problem of fast and accurate compressive image recovery.
method Inspired by D-AMP, developed LDAMP neural network architecture.
result LDAMP outperforms BM3D-AMP and NLR-CS in accuracy and run time.
Unsupervised image recovery using Stein's Unbiased Risk Estimator.
problem Learning from unlabeled and noisy data.
method Revisiting Stein's Unbiased Risk Estimator (SURE) for image recovery.
result SURE can be used to train CNNs for image denoising and recovery without ground truth data.