Abstract
In this chapter, a despeckling method which is based on the wavelet transformation and fast bilateral filter is introduced. According to the statistical properties of medical ultrasound image in the wavelet domain, an improved wavelet threshold function based on the universal wavelet threshold function is considered. The wavelet coefficients of noise-free signal and speckle noise are modeled as generalized Laplace distribution and Gaussian distribution, respectively. The Bayesian maximum a posteriori estimation is applied to obtain a new wavelet shrinkage algorithm. High-pass component speckle noise in the wavelet domain of ultrasound images is suppressed by the new shrinkage algorithm. Additionally, the coefficients of the low frequency signal in the wavelet domain are filtered by the fast bilateral filter, since the low-pass component of ultrasound images also contains some speckle noise. Compared with other de-speckling methods, experiments show that the proposed method has improved de-speckling performance for medical ultrasound images. It not only has better reduction performance than other methods but also can preserve image details such as the edge of lesions.
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Zhang, J., Cheng, Y. (2020). Wavelet and Fast Bilateral Filter Based Despeckling Method for Medical Ultrasound Images. In: Despeckling Methods for Medical Ultrasound Images. Springer, Singapore. https://doi.org/10.1007/978-981-15-0516-4_3
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DOI: https://doi.org/10.1007/978-981-15-0516-4_3
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