Denoising

Denoising is a task in image processing and computer vision that aims to remove or reduce noise from an image. Noise can be introduced into an image due to various reasons, such as camera sensor limitations, lighting conditions, and compression artifacts. The goal of denoising is to recover the original image, which is considered to be noise-free, from a noisy observation.

( Image credit: Beyond a Gaussian Denoiser )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1601–1610 of 7282 papers

Title	Date	Tasks	Status	Hype
Dual Adversarial Network: Toward Real-world Noise Removal and Noise Generation	Jul 12, 2020	DenoisingImage Denoising	CodeCode Available	1
Lightweight Modules for Efficient Deep Learning based Image Restoration	Jul 11, 2020	ClassificationDeep Learning	CodeCode Available	1
Designing and Training of A Dual CNN for Image Denoising	Jul 8, 2020	DenoisingImage Denoising	CodeCode Available	1
Learning Graph-Convolutional Representations for Point Cloud Denoising	Jul 6, 2020	Denoising	CodeCode Available	1
Accelerated MRI with Un-trained Neural Networks	Jul 6, 2020	compressed sensingDecoder	CodeCode Available	1
Speckle2Void: Deep Self-Supervised SAR Despeckling with Blind-Spot Convolutional Neural Networks	Jul 4, 2020	DenoisingSar Image Despeckling	CodeCode Available	1
Joint Frequency and Image Space Learning for MRI Reconstruction and Analysis	Jul 2, 2020	DenoisingImage Denoising	CodeCode Available	1
BiO-Net: Learning Recurrent Bi-directional Connections for Encoder-Decoder Architecture	Jul 1, 2020	DecoderDenoising	CodeCode Available	1
SACNN: Self-Attention Convolutional Neural Network for Low-Dose CT Denoising With Self-Supervised Perceptual Loss Network	Jul 1, 2020	Computed Tomography (CT)Denoising	CodeCode Available	1
A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game Encoding	Jun 26, 2020	compressed sensingDenoising	CodeCode Available	1

Show:10 25 50

← PrevPage 161 of 729Next →

All datasets Darmstadt Noise Dataset DIV2K DND iris

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	SINDy	PSNR	81	—	Unverified
2	Pixel-shuffling Downsampling	PSNR	38.4	—	Unverified
3	TWSC	PSNR	37.93	—	Unverified
4	CBDNet(Syn)	PSNR	37.57	—	Unverified
5	MCWNNM	PSNR	37.38	—	Unverified
6	Han et al	PSNR	35.95	—	Unverified
7	FFDNet	PSNR	34.4	—	Unverified
8	TNRD	PSNR	33.65	—	Unverified
9	CDnCNN-B	PSNR	32.43	—	Unverified
10	NLRN	PSNR	30.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DRUnet_Poisson_0.01	Average PSNR (dB)	33.92	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DRANet	Average PSNR	39.64	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PCNN+RL+HME	Average	84.61	—	Unverified