Additive white gaussian noise level estimation in SVD domain for images

Accurate estimation of Gaussian noise level is of fundamental interest in a wide variety of vision and image processing applications as it is critical to the processing techniques that follow. In this paper, a new effective noise level estimation method is proposed on the basis of the study of singu...

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Main Authors: Wei Liu., Weisi Lin.
Other Authors: School of Computer Engineering
Format: Article
Language:English
Published: 2013
Subjects:
Online Access:https://hdl.handle.net/10356/84494
http://hdl.handle.net/10220/18109
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-844942020-05-28T07:17:16Z Additive white gaussian noise level estimation in SVD domain for images Wei Liu. Weisi Lin. School of Computer Engineering DRNTU::Engineering::Computer science and engineering Accurate estimation of Gaussian noise level is of fundamental interest in a wide variety of vision and image processing applications as it is critical to the processing techniques that follow. In this paper, a new effective noise level estimation method is proposed on the basis of the study of singular values of noise-corrupted images. Two novel aspects of this paper address the major challenges in noise estimation: 1) the use of the tail of singular values for noise estimation to alleviate the influence of the signal on the data basis for the noise estimation process and 2) the addition of known noise to estimate the content-dependent parameter, so that the proposed scheme is adaptive to visual signals, thereby enabling a wider application scope of the proposed scheme. The analysis and experiment results demonstrate that the proposed algorithm can reliably infer noise levels and show robust behavior over a wide range of visual content and noise conditions, and that is outperforms relevant existing methods. 2013-12-05T06:33:14Z 2019-12-06T15:46:06Z 2013-12-05T06:33:14Z 2019-12-06T15:46:06Z 2013 2013 Journal Article Liu, W., & Lin, W. (2013). Additive white gaussian noise level estimation in SVD domain for images. IEEE transactions on image processing, 22(3), 872-883. 1057-7149 https://hdl.handle.net/10356/84494 http://hdl.handle.net/10220/18109 10.1109/TIP.2012.2219544 en IEEE transactions on image processing
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering
spellingShingle DRNTU::Engineering::Computer science and engineering
Wei Liu.
Weisi Lin.
Additive white gaussian noise level estimation in SVD domain for images
description Accurate estimation of Gaussian noise level is of fundamental interest in a wide variety of vision and image processing applications as it is critical to the processing techniques that follow. In this paper, a new effective noise level estimation method is proposed on the basis of the study of singular values of noise-corrupted images. Two novel aspects of this paper address the major challenges in noise estimation: 1) the use of the tail of singular values for noise estimation to alleviate the influence of the signal on the data basis for the noise estimation process and 2) the addition of known noise to estimate the content-dependent parameter, so that the proposed scheme is adaptive to visual signals, thereby enabling a wider application scope of the proposed scheme. The analysis and experiment results demonstrate that the proposed algorithm can reliably infer noise levels and show robust behavior over a wide range of visual content and noise conditions, and that is outperforms relevant existing methods.
author2 School of Computer Engineering
author_facet School of Computer Engineering
Wei Liu.
Weisi Lin.
format Article
author Wei Liu.
Weisi Lin.
author_sort Wei Liu.
title Additive white gaussian noise level estimation in SVD domain for images
title_short Additive white gaussian noise level estimation in SVD domain for images
title_full Additive white gaussian noise level estimation in SVD domain for images
title_fullStr Additive white gaussian noise level estimation in SVD domain for images
title_full_unstemmed Additive white gaussian noise level estimation in SVD domain for images
title_sort additive white gaussian noise level estimation in svd domain for images
publishDate 2013
url https://hdl.handle.net/10356/84494
http://hdl.handle.net/10220/18109
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