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

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), 2016. 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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Cite This Article
  • 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

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

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

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

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