Deep learning on image denoising: an overview
From MaRDI portal
Publication:2057732
DOI10.1016/j.neunet.2020.07.025zbMath1475.68324arXiv1912.13171OpenAlexW3047011367WikidataQ98629971 ScholiaQ98629971MaRDI QIDQ2057732
Wangmeng Zuo, Yong Xu, Lunke Fei, Wenxian Zheng, Chia-Wen Lin, Chunwei Tian
Publication date: 7 December 2021
Published in: Neural Networks (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1912.13171
Artificial neural networks and deep learning (68T07) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)
Related Items (4)
Image Denoising: The Deep Learning Revolution and Beyond—A Survey Paper ⋮ MFLP-PINN: a physics-informed neural network for multiaxial fatigue life prediction ⋮ Consensus guided incomplete multi-view spectral clustering ⋮ An hybrid denoising algorithm based on directional wavelet packets
Uses Software
Cites Work
- Beyond sparsity: the role of \(L_{1}\)-optimizer in pattern classification
- Neocognition: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position
- Robust learning with imperfect privileged information
- Extended tanh-function method and its applications to nonlinear equations
- Similarity and diversity induced paired projection for cross-modal retrieval
- Reducing the Dimensionality of Data with Neural Networks
- Large-Scale Machine Learning with Stochastic Gradient Descent
- Image restoration using a multilayer perceptron with a multilevel sigmoidal function
- $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
- Gradient Histogram Estimation and Preservation for Texture Enhanced Image Denoising
- External Prior Guided Internal Prior Learning for Real-World Noisy Image Denoising
- Class-Aware Fully Convolutional Gaussian and Poisson Denoising
- Waterloo Exploration Database: New Challenges for Image Quality Assessment Models
- Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
- Deep Convolutional Neural Network for Inverse Problems in Imaging
- Deep Convolutional Framelets: A General Deep Learning Framework for Inverse Problems
- Single Image Deraining Using Bilateral Recurrent Network
- Iterative Joint Image Demosaicking and Denoising Using a Residual Denoising Network
- Low-Light Image Enhancement via a Deep Hybrid Network
- FSIM: A Feature Similarity Index for Image Quality Assessment
- Nonlocally Centralized Sparse Representation for Image Restoration
- A Fast Learning Algorithm for Deep Belief Nets
- An Iterative Regularization Method for Total Variation-Based Image Restoration
This page was built for publication: Deep learning on image denoising: an overview