Color Image Denoising
27 papers with code • 61 benchmarks • 8 datasets
Datasets
Most implemented papers
Adversarial Distortion Learning for Medical Image Denoising
The proposed ADL consists of two auto-encoders: a denoiser and a discriminator.
Hypernetwork-Based Adaptive Image Restoration
Adaptive image restoration models can restore images with different degradation levels at inference time without the need to retrain the model.
iiTransformer: A Unified Approach to Exploiting Local and Non-Local Information for Image Restoration
The goal of image restoration is to recover a high-quality image from its degraded input.
KBNet: Kernel Basis Network for Image Restoration
In this paper, we propose a kernel basis attention (KBA) module, which introduces learnable kernel bases to model representative image patterns for spatial information aggregation.
Towards Resilient and Secure Smart Grids against PMU Adversarial Attacks: A Deep Learning-Based Robust Data Engineering Approach
In an attempt to provide reliable power distribution, smart grids integrate monitoring, communication, and control technologies for better energy consumption and management.
A Novel Truncated Norm Regularization Method for Multi-channel Color Image Denoising
However, those methods mostly ignore either the cross-channel difference or the spatial variation of noise, which limits their capacity in real world color image denoising.
A Theoretically Guaranteed Quaternion Weighted Schatten p-norm Minimization Method for Color Image Restoration
Very recently, a quaternion-based WNNM approach (QWNNM) has been developed to mitigate this issue, which is capable of representing the color image as a whole in the quaternion domain and preserving the inherent correlation among the three color channels.