A Novel Despeckling Method for Medical Ultrasound Images Based on the Nonsubsampled Shearlet and Guided Filter

Autor: Yun Cheng, Tian Zheng, Zhang Ju, Zhao Kailun, Xiu Xiaojie, Zhou Jun
Rok vydání: 2019
Předmět:
Zdroj: Circuits, Systems, and Signal Processing. 39:1449-1470
ISSN: 1531-5878
0278-081X
DOI: 10.1007/s00034-019-01201-2
Popis: Ultrasound diagnostic techniques are widely used in medical clinical diagnostics. However, the presence of speckle noise in the ultrasound imaging process reduces the image quality and creates inconvenience to the physician during clinical diagnosis. The ability to reduce the influence of speckle noise has important significance therefore in medical ultrasound image diagnosis. This paper offers a solution. It proposes a novel despeckling method based on nonsubsampled shearlet transformation and a guided filter. First, a nonsubsampled Laplacian pyramid filter is used to decompose the noisy image thus decomposing the image into high-frequency and low-frequency subbands. Under the direction of the non-sampling filter bank, a high-frequency subband multi-directional decomposition is obtained. Next, based on the threshold function and the correlation of the shearlet coefficients in the transformation domain, an improved threshold shrinkage algorithm is proposed to perform the threshold shrinkage processing on the shearlet coefficients of the high-frequency subbands. Finally, the low-frequency subbands in the transformation domain are processed by the guided filter, and a denoised ultrasonic image is obtained by the inverse transformation of the shearlet. So as to verify the effectiveness of the proposed method, experiments were conducted, and the results were compared to those of other existing denoising filters. These showed the proposed method performs more effectively at denoising and delivers clearer image detail.
Databáze: OpenAIRE
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