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基于自适应小波包的双边滤波去噪超声图像。

Adaptive wavelet packet-based de-speckling of ultrasound images with bilateral filter.

机构信息

Department of Instrumentation and Control Systems Engineering, PSG College of Technology, Peelamedu, Coimbatore, India.

出版信息

Ultrasound Med Biol. 2013 Dec;39(12):2463-76. doi: 10.1016/j.ultrasmedbio.2013.07.009. Epub 2013 Sep 21.

Abstract

A new adaptive wavelet packet-based approach to minimize speckle noise in ultrasound images is proposed. This method combines wavelet packet thresholding with a bilateral filter. Here, the best bases after wavelet packet decomposition are selected by comparing the first singular value of all sub-bands, and the noisy coefficients are thresholded using a modified NeighShrink technique. The algorithm is tested with various ultrasound images, and the results, in terms of peak signal-to-noise ratio and mean structural similarity values, are compared with those for some well-known de-speckling techniques. The simulation results indicate that the proposed method has better potential to minimize speckle noise and retain fine details of the ultrasound image.

摘要

提出了一种新的基于自适应小波包的方法来最小化超声图像中的斑点噪声。该方法将小波包阈值处理与双边滤波器相结合。在这里,通过比较所有子带的第一奇异值来选择最佳的小波包分解基,然后使用改进的 NeighShrink 技术对噪声系数进行阈值处理。该算法已在各种超声图像上进行了测试,并根据峰值信噪比和平均结构相似性值与一些知名的去斑技术进行了比较。仿真结果表明,该方法在最小化斑点噪声和保留超声图像的细节方面具有更好的潜力。

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