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A Review of Image Denoising Methods
2015
Journal of Engineering Science and Technology Review
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These methods have been categorized on the bases of techniques used. ...
Images can get corrupted by noise, there has been a great research effort which made solutions for this problem, a number of methods have been proposed. ...
Zhang [167] proposed fuzzy based impulse noise detection and removal by using long-range correlation among different image portions. ...
doi:10.25103/jestr.085.07
fatcat:4c4f3oz3wzakhaitav3k5ktdp4
Mixed image denoising using weighted coding and non-local similarity
2020
SN Applied Sciences
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This paper presents a denoising model by exploiting such a combination that uses an overcomplete dictionary by sparse based denoising scheme with suitable regularization terms. ...
Still, underlying noise that is predominant in the images reduces the quality. Additive white Gaussian noise (AWGN) and impulse noise are the most exploited types of noise. ...
A fuzzy metric-based filter is used to remove impulsive noise, while a fuzzy peer group method is used in the second stage to remove Gaussian noise. ...
doi:10.1007/s42452-020-2816-y
fatcat:o5rov3l4oneylouohaso3edoke
Restoration of Images with High-Density Impulsive Noise based on Sparse Approximation and Ant-colony Optimization
2020
IEEE Access
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The proposed method first uses the inverse-distance weighting-based prediction to estimate noise-recovered pixels. ...
In this work, we propose an image denoising approach, specifically for "salt-and-pepper noise," based on the optimized sparse approximation for restoring images contaminated by high-density impulse noise ...
Toh and Isa [3] developed a noise adaptive fuzzy switching median filter to remove impulse noise from corrupted images, obtaining a denoised image by using fuzzy computation via a weighted smoothing ...
doi:10.1109/access.2020.2995647
fatcat:f3airambzrbp7cua6zxmrh2dkq
Survey on mixed impulse and Gaussian denoising filters
2020
IET Image Processing
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The random noise model considered in this survey is the combined effect of impulse (salt and pepper) and Gaussian noise. ...
After describing the noise models, the denoising filters which are applied to the images are classified and explained according to their design structure, the type of filters they use, the noise level ...
The method in [68] uses both fuzzy switching filter and the bilateral filter to remove the impulse and Gaussian noise, respectively. ...
doi:10.1049/iet-ipr.2018.6335
fatcat:w44kcffh6vhmffi3hvgijlztfq
Neural-network-based Impulse Noise Removal Using Group-based Weighted Couple Sparse Representation
2018
KSII Transactions on Internet and Information Systems
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In the next stage, we use group-based weighted couple sparse representation to filter the noisy pixels. ...
Also, with the information of noisy pixel location, the proposed impulse-noise removal method performs better than the conventional methods, through the recovered images resulting in better quality. . ...
Schulte et al. also proposed the fuzzy random impulse noise reduction method (FRINRM) [13] , a two-step fuzzy filter that uses fuzzy logic to enhance images corrupted with IN. ...
doi:10.3837/tiis.2018.08.018
fatcat:mt7n56xtsrhebmsfa4jpn7ilmi
Smart Switching Bilateral Filter with Estimated Noise Characterization for Mixed Noise Removal
2019
Mathematical Problems in Engineering
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and 3D filtering (BM3D), nonlocal sparse representation (NCSR), and trilateral filter (TF). ...
In the first stage of SSBF, we propose a new scheme of noise estimation using domain weight (DW) pattern which characterizes the distribution of the different intensity between a considered pixel and its ...
sparse representation (NCSR) [29] , nonlocal regularization (WESNR) [9] and fuzzy impulsive additive noise suppression using sparse representation (F IANS SR) [30] , combine these methods in order ...
doi:10.1155/2019/5632145
fatcat:wvcejk6ltfdc7kknyqqy2nyy7i
Salt and Pepper Noise Removal with Noise Detection and a Patch-Based Sparse Representation
2014
Advances in Multimedia
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A denoising method by detecting noise candidates and enforcing image sparsity with a patch-based sparse representation is proposed. ...
First, noise candidates are detected and an initial guide image is obtained via an adaptive median filtering; second, a patch-based sparse representation is learnt from this guide image; third, a weightedl1 ...
PANO-Based Impulse Noise Removal with Noise Detection and a Weighted 1 -1 Regularization Model (PANO-ND). ...
doi:10.1155/2014/682747
fatcat:djm4wo7tivhkjlbjybjov6mfj4
Hybrid Regression Analysis based Technique for Removal of Impulse Noise from Gray-Scale Images
2014
International Journal of Computer Applications
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In this algorithm an uncertainty-based detector identifies which pixels are affected by impulse noise. Then, a Weighted Fuzzy Mean Filter is used for correction of noisy pixel from gray scale image. ...
Zhe Zhou [2] proposed a method and the name of method is Cloud Model filter, this method presents a novel adaptive detail-preserving filter for removing impulse noise from gray scale images. ...
Patch-based nonlocal operator with noise detection [9] uses Adaptive median filter for detection than learn patch-based sparse representation. Patch-based sparse is learnt from image. ...
doi:10.5120/18057-8987
fatcat:kn6y3nuij5aarixz7h23ewevhu
Real-time image processing systems using fuzzy and rough sets techniques
2018
Soft Computing - A Fusion of Foundations, Methodologies and Applications
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Multimedia systems are increasingly required to provide advanced real-time features with reliable performance and low cost. ...
In particular, real-time image processing techniques are used in a number of domains of science, technology, and business. ...
"Adaptive switching filter for impulse noise removal in digital content," a new fuzzy-rule-based impulse noise denoising method which removes unwanted artifacts and reconstructs original images is proposed ...
doi:10.1007/s00500-017-2999-3
fatcat:tlq5qkje6rei7cjots7i7qqzqu
Image De-noising with Machine Learning: A Review
2021
IEEE Access
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For impulse noise removal, Blind CNN, and CNN+PSO perform well. For mixed noise removal, WDL, EM-CNN, CNN, SDL, and Mixed CNN are prominent. ...
These de-noisers are compared using PSNR as quality assessment metric on some benchmark datasets. The best de-noising results for different noise type is discussed along with future prospects. ...
Removal
of
Gaussian-Impulse
noise
W-KSVD
[84]
Uses
maximum
likelihood estimation
framework
and
sparse
representations over
a trained dictionary
and uses a self-
determined
weighting
data ...
doi:10.1109/access.2021.3092425
fatcat:xirq6soukzchvaeiugcpgxnlqi
Image Restoration in Noisy Free Images Using Fuzzy Based Median Filtering and Adaptive Particle Swarm Optimization - Richardson-Lucy Algorithm
2017
International Journal of Intelligent Engineering and Systems
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The noise removed images from the FMF is appears to be so there is a need to restore the images with high quality. ...
In this paper, we have proposed adaptive methods for image restoration in which the input images are affected by noise which is removed by fuzzy based median filter (FMF). ...
The research work can be carried out further by employing techniques to remove noise up to high level, unless we are not successful in removing noise pixel we cannot boost noiseless pixels alone for restoration ...
doi:10.22266/ijies2017.0831.06
fatcat:fqcyowytmfcidintvbp3zv64fe
A Fast Iterative Method for Removing Impulsive Noise from Sparse Signals
[article]
2019
arXiv
pre-print
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Other Versions
As an application of this problem, we apply our algorithm for impulsive noise Salt-and-Pepper noise (SPN) and Random-Valued Impulsive Noise (RVIN)) removal from images and compare our results with other ...
The problem investigated in this paper arises in different applications such as impulsive noise removal from images, audios and videos, decomposition of low-rank and sparse components of matrices, and ...
In [22] , the Weighted Encoding with Sparse Nonlocal Regularization method (WESNR) is introduced which integrates a soft impulse detection and sparse non-local prior to remove mixed noise from images. ...
arXiv:1902.03988v2
fatcat:nstka7lfsjbe3orei5fkd4t6g4
Image Noise Handling Mechanism: An Analysis of Image Filtering Mechanisms
2018
International Journal for Research in Applied Science and Engineering Technology
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In order to tackle the issue noise handling mechanism are required to be incorporated within existing image handling mechanism. Filtering is one of the strategies associated with noise handling. ...
With the emergence of technology, information is represented in image form rather than textual form. The image capturing mechanisms may cause noise within the image. ...
This filter is easy and simple to implement and causes the noise to reduce significantly. High impulse and random noise is tackled using the fuzzy filter mechanism. ...
doi:10.22214/ijraset.2018.3104
fatcat:3uqrewcnifgetbtkl2fd6ri7aq
Elimination Noise from Image Using Machine Learning Techniques
2023
Journal of Image Processing and Intelligent Remote Sensing
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In this paper Image de-noising through K-SVD algorithm is presented by taking the RGB color with 256*256 sizes 24 bit standardize image. ...
The Image Processing system is mostly used because of their easy accessibility of powerful personal computers, bulk memory machines with graphics software and others visual application. ...
Filter used for denoising the image for corrupted with 'Impulse noise'. The performance can be evaluated through the simple 'PSNR and FSIM matrices'. ...
doi:10.55529/jipirs.36.27.36
fatcat:ymsu76k3ejf77olbi4c2ix6gye
A two-stage shearlet-based approach for the removal of random-valued impulse noise in images
2015
Journal of Visual Communication and Image Representation
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In this paper, we introduce a novel two-stage denoising method for the removal of random-valued impulse noise (RVIN) in images. ...
We present extensive numerical demonstrations to show that our approach is very effective to remove random-valued impulse noise without any significant loss of fine-scale detail. ...
[7] that uses a fuzzy weighting function with the non-local means algorithm to selectively pick pixels when calculating the pixel similarity. ...
doi:10.1016/j.jvcir.2015.07.014
fatcat:oybo4zh245dbnon62tvuiarvbi
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