Hybrid Deep Learning Framework for Reduction of Mixed Noise via Low Rank Noise Estimation

Hybrid Deep Learning Framework for Reduction of Mixed Noise via Low Rank Noise Estimation

In this paper, an innovative hybridized deep learning framework (EN-CNN) is presented for image noise reduction where the noise originates from heterogeneous sources. More specifically, EN-CNN is applied to the benchmark natural images affected by a mixture of additive white gaussian noise (AWGN) an...

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Bibliographic Details
Main Authors: Dai-Gyoung Kim, Yasir Ali, Muhammad Asif Farooq, Asif Mushtaq, Muhammad Ahmad Abdul Rehman, Zahid Hussain Shamsi
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Image denoising
deep learning
convolution neural network
low rank estimation
impulsive noise
Gaussian noise
Online Access:https://ieeexplore.ieee.org/document/9762953/

Internet

https://ieeexplore.ieee.org/document/9762953/

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