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Despeckle Filtering of Medical Ultrasonic Images Using Wavelet and Guided Filter

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Despeckling Methods for Medical Ultrasound Images

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Abstract

In this chapter, a new de-noising method based on an improved wavelet filter and guided filter is presented. The Bayesian maximum a posteriori estimation is applied to obtain a wavelet shrinkage algorithm. The coefficients of the low frequency sub-band in the wavelet domain are filtered by guided filter. The filtered image is then obtained by using the inverse wavelet transformation. Experiments with the comparison of the other seven de-speckling filters are conducted. The results show that the proposed method not only has a strong de-speckling ability, but also keeps the image details, such as the edge of a lesion.

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Author information

Authors and Affiliations

  1. Zhijiang College of Zhejiang University of Technology, Shaoxing, Zhejiang, China

    Ju Zhang

  2. Department of Ultrasound, Zhejiang Hospital, Hangzhou, Zhejiang, China

    Yun Cheng

Authors
  1. Ju Zhang
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  2. Yun Cheng
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Correspondence to Ju Zhang .

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Zhang, J., Cheng, Y. (2020). Despeckle Filtering of Medical Ultrasonic Images Using Wavelet and Guided Filter. In: Despeckling Methods for Medical Ultrasound Images. Springer, Singapore. https://doi.org/10.1007/978-981-15-0516-4_4

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  • DOI: https://doi.org/10.1007/978-981-15-0516-4_4

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-0515-7

  • Online ISBN: 978-981-15-0516-4

  • eBook Packages: EngineeringEngineering (R0)

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