SOTAVerified

Image Restoration

Image Restoration is a family of inverse problems for obtaining a high quality image from a corrupted input image. Corruption may occur due to the image-capture process (e.g., noise, lens blur), post-processing (e.g., JPEG compression), or photography in non-ideal conditions (e.g., haze, motion blur).

Source: Blind Image Restoration without Prior Knowledge

Papers

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Showing 1401–1450 of 1459 papers

TitleStatusHype
Low-rank Matrix Factorization under General Mixture Noise Distributions—0
Sparse Representation of a Blur Kernel for Blind Image Restoration—0
Conformal and Low-Rank Sparse Representation for Image Restoration—0
The Return of the Gating Network: Combining Generative Models and Discriminative Training in Natural Image Priors—0
Loss Functions for Neural Networks for Image ProcessingCode0
Color graph based wavelet transform with perceptual information—0
Wavelet Frame Based Image Restoration Using Sparsity, Nonlocal and Support Prior of Frame Coefficients—0
Fast and Accurate Poisson Denoising with Optimized Nonlinear Diffusion—0
Bregman Iteration for Correspondence Problems: A Study of Optical Flow—0
Matrix Factorisation with Linear Filters—0
A Total Fractional-Order Variation Model for Image Restoration with Non-homogeneous Boundary Conditions and its Numerical Solution—0
Improving Image Restoration with Soft-Rounding—0
Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration—0
Deep Networks for Image Super-Resolution with Sparse Prior—0
Coercive functions from a topological viewpoint and properties of minimizing sets of convex functions appearing in image restoration—0
UniHIST: A Unified Framework for Image Restoration With Marginal Histogram Constraints—0
L0TV: A New Method for Image Restoration in the Presence of Impulse Noise—0
Diffusion Methods for Classification with Pairwise Relationships—0
The structure of optimal parameters for image restoration problems—0
Segmentation and Restoration of Images on Surfaces by Parametric Active Contours with Topology Changes—0
On learning optimized reaction diffusion processes for effective image restorationCode0
Statistical Analysis of Loopy Belief Propagation in Random Fields—0
Designing A Composite Dictionary Adaptively From Joint Examples—0
Concept for a CMOS Image Sensor Suited for Analog Image Pre-Processing—0
Image denoising based on improved data-driven sparse representation—0
Inexact Alternating Direction Method Based on Newton descent algorithm with Application to Poisson Image Deblurring—0
An Approach for Reducing Outliers of Non Local Means Image Denoising Filter—0
Bayesian Image Restoration for Poisson Corrupted Image using a Latent Variational Method with Gaussian MRFCode0
Analytical Comparison of Noise Reduction Filters for Image Restoration Using SNR Estimation—0
Higher-order MRFs based image super resolution: why not MAP?—0
Recent Progress in Image Deblurring—0
Compression, Restoration, Re-sampling, Compressive Sensing: Fast Transforms in Digital Imaging—0
Image Inpainting Using Directional Tensor Product Complex Tight Framelets—0
Solving QVIs for Image Restoration with Adaptive Constraint Sets—0
Adaptive Mesh Representation and Restoration of Biomedical Images—0
Truncated Nuclear Norm Minimization for Image Restoration Based On Iterative Support Detection—0
Shrinkage Fields for Effective Image Restoration—0
Deblurring Text Images via L0-Regularized Intensity and Gradient Prior—0
Covariance Trees for 2D and 3D Processing—0
Multi-Shot Imaging: Joint Alignment, Deblurring and Resolution-Enhancement—0
Group-based Sparse Representation for Image RestorationCode0
Image Restoration Using Joint Statistical Modeling in Space-Transform Domain—0
Variational Image Segmentation Model Coupled with Image Restoration Achievements—0
A higher-order MRF based variational model for multiplicative noise reduction—0
Cascades of Regression Tree Fields for Image Restoration—0
A convergence proof of the split Bregman method for regularized least-squares problems—0
Revisiting loss-specific training of filter-based MRFs for image restoration—0
Insights into analysis operator learning: From patch-based sparse models to higher-order MRFs—0
Image Restoration using Total Variation with Overlapping Group Sparsity—0
A Robust Variational Model for Positive Image Deconvolution—0
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All datasetsCDD-11UHDM.

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1OneRestoreAverage PSNR (dB)28.72—Unverified
2SRUDCAverage PSNR (dB)27.64—Unverified
3RestormerAverage PSNR (dB)26.99—Unverified
4WGWSNetAverage PSNR (dB)26.96—Unverified
5DGUNetAverage PSNR (dB)26.92—Unverified
6OKNetAverage PSNR (dB)26.33—Unverified
7MIRNetAverage PSNR (dB)25.97—Unverified
8PromptIRAverage PSNR (dB)25.9—Unverified
9MPRNetAverage PSNR (dB)25.47—Unverified
10MIRNetv2Average PSNR (dB)25.37—Unverified
#ModelMetricClaimedVerifiedStatus
1ESDNet-LPSNR22.42—Unverified
2ESDNetPSNR22.12—Unverified
#ModelMetricClaimedVerifiedStatus
1730L37—Unverified