Deducing Local Influence Neighbourhoods with Application to Edge-Preserving Image Denoising

2007 ◽  
pp. 180-190
Author(s):  
Ashish Raj ◽  
Karl Young ◽  
Kailash Thakur
Keyword(s):  
Image Denoising ◽  
Local Influence ◽  
Edge Preserving

Joint Image Denoising with Gradient Direction and Edge-Preserving Regularization

2021 ◽  
pp. 108506
Author(s):  
Pengliang Li ◽  
Junli Liang ◽  
Miaohua Zhang ◽  
Wen Fan ◽  
Guoyang Yu
Keyword(s):  
Image Denoising ◽  
Edge Preserving ◽  
Gradient Direction

scholarly journals A well-posed multiscale regularization scheme for digital image denoising

2011 ◽  
Vol 21 (4) ◽  
pp. 769-777 ◽  
Author(s):  
V. Prasath
Keyword(s):  
Image Denoising ◽  
Digital Image ◽  
Regularization Parameter ◽  
Input Image ◽  
Smooth Transition ◽  
Functions Of Bounded Variation ◽  
Edge Preserving ◽  
Regularization Scheme ◽  
Adaptive Parameter ◽  
Well Posed

A well-posed multiscale regularization scheme for digital image denoisingWe propose an edge adaptive digital image denoising and restoration scheme based on space dependent regularization. Traditional gradient based schemes use an edge map computed from gradients alone to drive the regularization. This may lead to the oversmoothing of the input image, and noise along edges can be amplified. To avoid these drawbacks, we make use of a multiscale descriptor given by a contextual edge detector obtained from local variances. Using a smooth transition from the computed edges, the proposed scheme removes noise in flat regions and preserves edges without oscillations. By incorporating a space dependent adaptive regularization parameter, image smoothing is driven along probable edges and not across them. The well-posedness of the corresponding minimization problem is proved in the space of functions of bounded variation. The corresponding gradient descent scheme is implemented and further numerical results illustrate the advantages of using the adaptive parameter in the regularization scheme. Compared with similar edge preserving regularization schemes, the proposed adaptive weight based scheme provides a better multiscale edge map, which in turn produces better restoration.

scholarly journals Edge-Preserving Image Denoising via Group Coordinate Descent on the GPU

2015 ◽  
Vol 24 (4) ◽  
pp. 1273-1281 ◽  
Author(s):  
Madison Gray McGaffin ◽  
Jeffrey A. Fessler
Keyword(s):  
Image Denoising ◽  
Coordinate Descent ◽  
Edge Preserving

scholarly journals Edge-preserving image denoising

2018 ◽  
Vol 12 (8) ◽  
pp. 1394-1401 ◽  
Author(s):  
Fenghua Guo ◽  
Caiming Zhang ◽  
Mingli Zhang
Keyword(s):  
Image Denoising ◽  
Edge Preserving

scholarly journals Edge-preserving color image denoising through tensor voting

2011 ◽  
Vol 115 (11) ◽  
pp. 1536-1551 ◽  
Author(s):  
Rodrigo Moreno ◽  
Miguel Angel Garcia ◽  
Domenec Puig ◽  
Carme Julià
Keyword(s):  
Image Denoising ◽  
Color Image ◽  
Tensor Voting ◽  
Edge Preserving ◽  
Color Image Denoising
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