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Image Deconvolution

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Showing 26–50 of 78 papers

TitleStatusHype
Properties on n-dimensional convolution for image deconvolution—0
Reconstructing the Image Scanning Microscopy Dataset: an Inverse Problem—0
Reconstruction of Enhanced Ultrasound Images From Compressed Measurements Using Simultaneous Direction Method of Multipliers—0
Learning to See Through Dazzle—0
Self-Supervised Single-Image Deconvolution with Siamese Neural Networks—0
Super Resolution image reconstructs via total variation-based image deconvolution: a majorization-minimization approach—0
The Empirical Watershed Wavelet—0
The Secrets of Non-Blind Poisson Deconvolution—0
Three dimensional blind image deconvolution for fluorescence microscopy using generative adversarial networks—0
VDIP-TGV: Blind Image Deconvolution via Variational Deep Image Prior Empowered by Total Generalized Variation—0
Video Super-Resolution via Deep Draft-Ensemble Learning—0
Whiteness-based bilevel learning of regularization parameters in imaging—0
Deep Learning-Based Image Recovery and Pose Estimation for Resident Space Objects—0
Deep Learning for Handling Kernel/model Uncertainty in Image Deconvolution—0
DeepRLS: A Recurrent Network Architecture with Least Squares Implicit Layers for Non-blind Image Deconvolution—0
DELAD: Deep Landweber-guided deconvolution with Hessian and sparse prior—0
Directional Mean Curvature for Textured Image Demixing—0
Douglas-Rachford Networks: Learning Both the Image Prior and Data Fidelity Terms for Blind Image Deconvolution—0
Dual Domain Filters Based Texture and Structure Preserving Image Non-Blind Deconvolution—0
Echoes in the Noise: Posterior Samples of Faint Galaxy Surface Brightness Profiles with Score-Based Likelihoods and Priors—0
Edge-Based Blur Kernel Estimation Using Sparse Representation and Self-Similarity—0
Fast Image Deconvolution using Hyper-Laplacian Priors—0
FTVd is beyond Fast Total Variation regularized Deconvolution—0
Ground-based image deconvolution with Swin Transformer UNet—0
Guided Filter based Edge-preserving Image Non-blind Deconvolution—0
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