loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Asif Khan and Mahmoud R. El-Sakka

Affiliation: The University of Western Ontario, Canada

ISBN: 978-989-758-175-5

Keyword(s): Image Denoising, Additive Gaussian Noise, Non-local Means, Two-stage Non-local Means, Spatial Domain Denoising.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Image Enhancement and Restoration ; Image Formation and Preprocessing

Abstract: Non-local means (NLM) is a popular image denoising scheme for reducing additive Gaussian noise. It uses a patch-based approach to find similar regions within a search neighborhood and estimates the denoised pixel based on the weighted average of all pixels in the neighborhood. All weights are considered for averaging, irrespective of the value of the weights. This paper proposes an improved variant of the original NLM scheme by thresholding the weights of the pixels within the search neighborhood, where the thresholded weights are used in the averaging step. The threshold value is adapted based on the noise level of a given image. The proposed method is used as a two-step approach for image denoising. In the first step the proposed method is applied to generate a basic estimate of the denoised image. The second step applies the proposed method once more but with different smoothing strength. Experiments show that the denoising performance of the proposed method is better than that of the original NLM scheme, and its variants. It also outperforms the state-of-the-art image denoising scheme, BM3D, but only at low noise levels (sigma <= 80). (More)

PDF ImageFull Text

Download
Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.234.51.17

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Khan, A. and El-Sakka, M. (2016). Non-local Means using Adaptive Weight Thresholding.In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 67-76. DOI: 10.5220/0005787100670076

@conference{visapp16,
author={Asif Khan. and Mahmoud R. El{-}Sakka.},
title={Non-local Means using Adaptive Weight Thresholding},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)},
year={2016},
pages={67-76},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005787100670076},
isbn={978-989-758-175-5},
}

TY - CONF

JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)
TI - Non-local Means using Adaptive Weight Thresholding
SN - 978-989-758-175-5
AU - Khan, A.
AU - El-Sakka, M.
PY - 2016
SP - 67
EP - 76
DO - 10.5220/0005787100670076

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.