Cluster based Non-Local Filters for Colour Image denoising

2018 ◽  
Vol 2 (3) ◽  
pp. 1
Author(s):  
RAJU G ◽  
SUGANDHI K ◽  
FARHA FATINA WAHID
Keyword(s):  
Image Denoising ◽  
Colour Image ◽  
Non Local ◽  
Local Filters

Cluster-based non-local filters for colour image denoising

2018 ◽  
Vol 2 (3) ◽  
pp. 185
Author(s):  
Farha Fatina Wahid ◽  
K. Sugandhi ◽  
G. Raju
Keyword(s):  
Image Denoising ◽  
Colour Image ◽  
Non Local ◽  
Local Filters

Non-local dual image denoising

2014 ◽  
Author(s):  
N. Pierazzo ◽  
M. Lebrun ◽  
M.E. Rais ◽  
J.M. Morel ◽  
G. Facciolo
Keyword(s):  
Image Denoising ◽  
Non Local ◽  
Dual Image

Automated Image Denoising Model: Contribution Towards Optimized Internal and External Basis

2021 ◽  
pp. 2150051
Author(s):  
S. Elavaar Kuzhali ◽  
D. S. Suresh
Keyword(s):  
Image Denoising ◽  
Image Patch ◽  
The Past ◽  
Local Means ◽  
Hybrid Optimization Algorithm ◽  
Proposed Model ◽  
Processing Step ◽  
Non Local ◽  
Chicken Swarm Optimization ◽  
Selection Of

For handling digital images for various applications, image denoising is considered as a fundamental pre-processing step. Diverse image denoising algorithms have been introduced in the past few decades. The main intent of this proposal is to develop an effective image denoising model on the basis of internal and external patches. This model adopts Non-local means (NLM) for performing the denoising, which uses redundant information of the image in pixel or spatial domain to reduce the noise. While performing the image denoising using NLM, “denoising an image patch using the other noisy patches within the noisy image is done for internal denoising and denoising a patch using the external clean natural patches is done for external denoising”. Here, the selection of optimal block from the entire datasets including internal noisy images and external clean natural images is decided by a new hybrid optimization algorithm. The two renowned optimization algorithms Chicken Swarm Optimization (CSO), and Dragon Fly Algorithm (DA) are merged, and the new hybrid algorithm Rooster-based Levy Updated DA (RLU-DA) is adopted. The experimental results in terms of some relevant performance measures show the promising results of the proposed model with remarkable stability and high accuracy.

scholarly journals Brain MR image denoising for Rician noise using pre-smooth non-local means filter

2015 ◽  
Vol 14 (1) ◽  
pp. 2 ◽  
Author(s):  
Jian Yang ◽  
Jingfan Fan ◽  
Danni Ai ◽  
Shoujun Zhou ◽  
Songyuan Tang ◽  
...  
Keyword(s):  
Image Denoising ◽  
Rician Noise ◽  
Mr Image ◽  
Local Means ◽  
Non Local
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