In this paper we propose a denoising technique based on non-local means using an image similarity measure. The idea is to use the SVD-based image quality metric as a measure of neighborhood similarity. This measure is then used in the computation of the spatial Gaussian weighting kernel. We also develop an optimization computation scheme using a par-allel architecture in order to accelerate the filtering process on different machines or different cores on the same machine. The obtained results are very promising
In non-local means (NLM), each pixel is denoised by performing a weighted averaging of its neighbour...
A new multiscale implementation of nonlocal means filtering (MHNLM) for image denoising is proposed....
The random noise arising from the acquisition process of magnetic resonance images negatively influe...
Abstract — Here in this Paper a new algorithm probable nonlocal means (PNLM) method for image denois...
National audienceThe Non-Local Means (NLM) image denoising algorithm pushed the limits of denoising....
Perceptually inspired image processing has been an emerging field of study in recent years. Here we ...
Parameter setting and information redundancy are essential issues for the non-local means (NLM) algo...
We present in this paper a new denoising method called non-local means. The method is based on a sim...
The non-local means (NLM) denoising method replaces each pixel by the weighted average of pixels wit...
Visual information transmitted in the form of digital images is becoming a major method of communica...
An improved image denoising technique based on the nonlocal means (NL-means) algorithm is investigat...
Abstract We propose in this paper an extension of the Non-Local Means (NL-Means) denoising algorithm...
For the non-local denoising approach presented by Buades et al., remarkable denoising results are ob...
Abstract — Noise removal and image enhancement are the important tasks addressed by many Image Proce...
For the non-local denoising approach presented by Buades et al., remarkable denoising results are ob...
In non-local means (NLM), each pixel is denoised by performing a weighted averaging of its neighbour...
A new multiscale implementation of nonlocal means filtering (MHNLM) for image denoising is proposed....
The random noise arising from the acquisition process of magnetic resonance images negatively influe...
Abstract — Here in this Paper a new algorithm probable nonlocal means (PNLM) method for image denois...
National audienceThe Non-Local Means (NLM) image denoising algorithm pushed the limits of denoising....
Perceptually inspired image processing has been an emerging field of study in recent years. Here we ...
Parameter setting and information redundancy are essential issues for the non-local means (NLM) algo...
We present in this paper a new denoising method called non-local means. The method is based on a sim...
The non-local means (NLM) denoising method replaces each pixel by the weighted average of pixels wit...
Visual information transmitted in the form of digital images is becoming a major method of communica...
An improved image denoising technique based on the nonlocal means (NL-means) algorithm is investigat...
Abstract We propose in this paper an extension of the Non-Local Means (NL-Means) denoising algorithm...
For the non-local denoising approach presented by Buades et al., remarkable denoising results are ob...
Abstract — Noise removal and image enhancement are the important tasks addressed by many Image Proce...
For the non-local denoising approach presented by Buades et al., remarkable denoising results are ob...
In non-local means (NLM), each pixel is denoised by performing a weighted averaging of its neighbour...
A new multiscale implementation of nonlocal means filtering (MHNLM) for image denoising is proposed....
The random noise arising from the acquisition process of magnetic resonance images negatively influe...