Linear Filtering and Total Variation De-noising of Composite Noises: Different Architectures and Simulation Study

Fateme Taherkhani; Mohammad Jalal Rastegar Fatemi; Yousef Ganjdanesh

doi:doi:10.11648/j.cssp.20150406.11

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Linear Filtering and Total Variation De-noising of Composite Noises: Different Architectures and Simulation Study

Fateme Taherkhani, Mohammad Jalal Rastegar Fatemi, Yousef Ganjdanesh

Published in Science Journal of Circuits, Systems and Signal Processing (Volume 4, Issue 6)

Received: 17 November 2015 Accepted: 23 December 2015 Published: 15 January 2016

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Abstract

Combined techniques consisting of traditional linear filtering and total variation de-noising are studied to de-noise images polluted with composite noises from different sources. Series and parallel approaches are compared theoretically. Some further discussions are given about parameters and their effect on the optimization problem. A simultaneous method is proposed and simulated using the convex optimization toolbox, comparing different alternative methods with respect to signal to noise ratio and error covariance matrix. The proposed method could be used to enhance the smoothing performance.

Published in	Science Journal of Circuits, Systems and Signal Processing (Volume 4, Issue 6)
DOI	10.11648/j.cssp.20150406.11
Page(s)	55-59
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Image Processing, Total Variation De-noising, Total Variation Smoothing, Linear Filter, Combined Linear Filtering and Total Variation De-noising

References

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Fateme Taherkhani, Mohammad Jalal Rastegar Fatemi, Yousef Ganjdanesh. (2016). Linear Filtering and Total Variation De-noising of Composite Noises: Different Architectures and Simulation Study. Science Journal of Circuits, Systems and Signal Processing, 4(6), 55-59. https://doi.org/10.11648/j.cssp.20150406.11

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ACS Style

Fateme Taherkhani; Mohammad Jalal Rastegar Fatemi; Yousef Ganjdanesh. Linear Filtering and Total Variation De-noising of Composite Noises: Different Architectures and Simulation Study. Sci. J. Circuits Syst. Signal Process. 2016, 4(6), 55-59. doi: 10.11648/j.cssp.20150406.11

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AMA Style

Fateme Taherkhani, Mohammad Jalal Rastegar Fatemi, Yousef Ganjdanesh. Linear Filtering and Total Variation De-noising of Composite Noises: Different Architectures and Simulation Study. Sci J Circuits Syst Signal Process. 2016;4(6):55-59. doi: 10.11648/j.cssp.20150406.11

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@article{10.11648/j.cssp.20150406.11,
  author = {Fateme Taherkhani and Mohammad Jalal Rastegar Fatemi and Yousef Ganjdanesh},
  title = {Linear Filtering and Total Variation De-noising of Composite Noises: Different Architectures and Simulation Study},
  journal = {Science Journal of Circuits, Systems and Signal Processing},
  volume = {4},
  number = {6},
  pages = {55-59},
  doi = {10.11648/j.cssp.20150406.11},
  url = {https://doi.org/10.11648/j.cssp.20150406.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cssp.20150406.11},
  abstract = {Combined techniques consisting of traditional linear filtering and total variation de-noising are studied to de-noise images polluted with composite noises from different sources. Series and parallel approaches are compared theoretically. Some further discussions are given about parameters and their effect on the optimization problem. A simultaneous method is proposed and simulated using the convex optimization toolbox, comparing different alternative methods with respect to signal to noise ratio and error covariance matrix. The proposed method could be used to enhance the smoothing performance.},
 year = {2016}
}

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TY  - JOUR
T1  - Linear Filtering and Total Variation De-noising of Composite Noises: Different Architectures and Simulation Study
AU  - Fateme Taherkhani
AU  - Mohammad Jalal Rastegar Fatemi
AU  - Yousef Ganjdanesh
Y1  - 2016/01/15
PY  - 2016
N1  - https://doi.org/10.11648/j.cssp.20150406.11
DO  - 10.11648/j.cssp.20150406.11
T2  - Science Journal of Circuits, Systems and Signal Processing
JF  - Science Journal of Circuits, Systems and Signal Processing
JO  - Science Journal of Circuits, Systems and Signal Processing
SP  - 55
EP  - 59
PB  - Science Publishing Group
SN  - 2326-9073
UR  - https://doi.org/10.11648/j.cssp.20150406.11
AB  - Combined techniques consisting of traditional linear filtering and total variation de-noising are studied to de-noise images polluted with composite noises from different sources. Series and parallel approaches are compared theoretically. Some further discussions are given about parameters and their effect on the optimization problem. A simultaneous method is proposed and simulated using the convex optimization toolbox, comparing different alternative methods with respect to signal to noise ratio and error covariance matrix. The proposed method could be used to enhance the smoothing performance.
VL  - 4
IS  - 6
ER  -

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Author Information

Fateme Taherkhani

Department of Electrical Engineering, Colledge of Technical and Engineering, Saveh Branch, Islamic Azad University, Saveh, Iran
Mohammad Jalal Rastegar Fatemi

Department of Electrical Engineering, Colledge of Technical and Engineering, Saveh Branch, Islamic Azad University, Saveh, Iran
Yousef Ganjdanesh

Department of Electrical Engineering, Colledge of Technical and Engineering, Saveh Branch, Islamic Azad University, Saveh, Iran

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APA Style

Fateme Taherkhani, Mohammad Jalal Rastegar Fatemi, Yousef Ganjdanesh. (2016). Linear Filtering and Total Variation De-noising of Composite Noises: Different Architectures and Simulation Study. Science Journal of Circuits, Systems and Signal Processing, 4(6), 55-59. https://doi.org/10.11648/j.cssp.20150406.11

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ACS Style

Fateme Taherkhani; Mohammad Jalal Rastegar Fatemi; Yousef Ganjdanesh. Linear Filtering and Total Variation De-noising of Composite Noises: Different Architectures and Simulation Study. Sci. J. Circuits Syst. Signal Process. 2016, 4(6), 55-59. doi: 10.11648/j.cssp.20150406.11

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AMA Style

Fateme Taherkhani, Mohammad Jalal Rastegar Fatemi, Yousef Ganjdanesh. Linear Filtering and Total Variation De-noising of Composite Noises: Different Architectures and Simulation Study. Sci J Circuits Syst Signal Process. 2016;4(6):55-59. doi: 10.11648/j.cssp.20150406.11

Copy | Download

@article{10.11648/j.cssp.20150406.11,
  author = {Fateme Taherkhani and Mohammad Jalal Rastegar Fatemi and Yousef Ganjdanesh},
  title = {Linear Filtering and Total Variation De-noising of Composite Noises: Different Architectures and Simulation Study},
  journal = {Science Journal of Circuits, Systems and Signal Processing},
  volume = {4},
  number = {6},
  pages = {55-59},
  doi = {10.11648/j.cssp.20150406.11},
  url = {https://doi.org/10.11648/j.cssp.20150406.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cssp.20150406.11},
  abstract = {Combined techniques consisting of traditional linear filtering and total variation de-noising are studied to de-noise images polluted with composite noises from different sources. Series and parallel approaches are compared theoretically. Some further discussions are given about parameters and their effect on the optimization problem. A simultaneous method is proposed and simulated using the convex optimization toolbox, comparing different alternative methods with respect to signal to noise ratio and error covariance matrix. The proposed method could be used to enhance the smoothing performance.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - Linear Filtering and Total Variation De-noising of Composite Noises: Different Architectures and Simulation Study
AU  - Fateme Taherkhani
AU  - Mohammad Jalal Rastegar Fatemi
AU  - Yousef Ganjdanesh
Y1  - 2016/01/15
PY  - 2016
N1  - https://doi.org/10.11648/j.cssp.20150406.11
DO  - 10.11648/j.cssp.20150406.11
T2  - Science Journal of Circuits, Systems and Signal Processing
JF  - Science Journal of Circuits, Systems and Signal Processing
JO  - Science Journal of Circuits, Systems and Signal Processing
SP  - 55
EP  - 59
PB  - Science Publishing Group
SN  - 2326-9073
UR  - https://doi.org/10.11648/j.cssp.20150406.11
AB  - Combined techniques consisting of traditional linear filtering and total variation de-noising are studied to de-noise images polluted with composite noises from different sources. Series and parallel approaches are compared theoretically. Some further discussions are given about parameters and their effect on the optimization problem. A simultaneous method is proposed and simulated using the convex optimization toolbox, comparing different alternative methods with respect to signal to noise ratio and error covariance matrix. The proposed method could be used to enhance the smoothing performance.
VL  - 4
IS  - 6
ER  -

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