Single Image Denoising via a New Lightweight Learning-Based Model-Reference-Cited by-同舟云学术

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Single Image Denoising via a New Lightweight Learning-Based Model

Published:2024 Issue: Volume:12 Page:121077-121092
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Rezvani Sadjad¹^ORCID,Soleymani Siahkar Fatemeh²,Rezvani Yasin¹^ORCID,Alavi Gharahbagh Abdorreza³^ORCID,Abolghasemi Vahid⁴^ORCID

Affiliation:

1. Faculty of Computer Engineering, Shahrood University of Technology, Shahrud, Iran

2. Faculty of Electrical Engineering, Shahid Beheshti University, Tehran, Iran

3. Faculty of Electrical and Computer Engineering, Islamic Azad University, Shahrud, Iran

4. School of Computer Science and Electronic Engineering, University of Essex, Colchester, U.K.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10654252.pdf?arnumber=10654252

Reference59 articles.

1. A comprehensive survey on impulse and Gaussian denoising filters for digital images

2. Task-Oriented GAN for PolSAR Image Classification and Clustering

3. Collaborative Deconvolutional Neural Networks for Joint Depth Estimation and Semantic Segmentation

4. MTU-Net: Multilevel TransUNet for Space-Based Infrared Tiny Ship Detection

5. A coarse-to-fine multi-scale feature hybrid low-dose CT denoising network

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