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Non-subsampled Contourlet Transform-Based Image Denoising in Ultrasound Images Using Elliptical Directional Windows and Block-Based Noise Estimation

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Intelligent Computing, Networking, and Informatics

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 243))

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Abstract

Speckle noise reduction is an important preprocessing stage for ultrasound medical image processing. In this paper, a despeckling algorithm is proposed based on non-subsampled contourlet transform (NSCT). This transform has the property of high directionality, anisotropy, and translation invariance which can be controlled by non-subsampled filter banks. This paper aims to estimate the noise-free coefficients in the directional subband by applying minimum mean square estimate (MMSE). Signal variance is estimated from the elliptical directional window, and noise variance is estimated from block-based approach and is compared with the MAD approach. Experimental results of proposed method are compared with existing methods in terms of signal-to-noise ratio (SNR) and edge preservation index.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Pondicherry Engineering College, Puducherry, India

    J. Jai Jaganath Babu & Gnanou Florence Sudha

Authors
  1. J. Jai Jaganath Babu
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  2. Gnanou Florence Sudha
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Corresponding author

Correspondence to J. Jai Jaganath Babu .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering, National Institute of Technology Rourkela, Rourkela, Orissa, India

    Durga Prasad Mohapatra

  2. Computer Science and Engineering, SOA University, Bhubaneswar, India

    Srikanta Patnaik

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Babu, J.J.J., Sudha, G.F. (2014). Non-subsampled Contourlet Transform-Based Image Denoising in Ultrasound Images Using Elliptical Directional Windows and Block-Based Noise Estimation. In: Mohapatra, D.P., Patnaik, S. (eds) Intelligent Computing, Networking, and Informatics. Advances in Intelligent Systems and Computing, vol 243. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1665-0_23

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  • DOI: https://doi.org/10.1007/978-81-322-1665-0_23

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-1664-3

  • Online ISBN: 978-81-322-1665-0

  • eBook Packages: EngineeringEngineering (R0)

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