Affiliations: Department of Electronics and Computer Engineering, Hanyang University, Seoul, South Korea
Correspondence:
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Corresponding author: Jechang Jeong, Department of Electronics and Computer Engineering, Hanyang University, 222, Wangsimni-ro, Seongdong-gu, Seoul 04763, South Korea. E-mail: jjeong@hanyang.ac.kr.
Abstract: Ultrasound imaging has been used for diagnosing lesions in the human body. In the process of acquiring ultrasound images, speckle noise may occur, affecting image quality and auto-lesion classification. Despite the efforts to resolve this, conventional algorithms exhibit poor speckle noise removal and edge preservation performance. Accordingly, in this study, a novel algorithm is proposed based on speckle reducing anisotropic diffusion (SRAD) and a Bayes threshold in the wavelet domain. In this algorithm, SRAD is employed as a preprocessing filter, and the Bayes threshold is used to remove the residual noise in the resulting image. Compared to the conventional filtering techniques, experimental results showed that the proposed algorithm exhibited superior performance in terms of peak signal-to-noise ratio (average = 28.61 dB) and structural similarity (average = 0.778).
