Dual-tree wavelet based algorithm for speckle reduction and edge enhancement in ultrasound images

W. Yen, S. Tai
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引用次数: 2

Abstract

Ultrasound images are the important bases of disease diagnostic. Unfortunately, the qualities of ultrasound images are generally limited due to speckle noises. Speckle reduction is an important pre-processing step in the ultrasound image feature extraction, analysis and recognition. In this paper, we present an approach for ultrasound image enhancement. It is designed to utilize the three technologies: the separability and multiresolution properties of the wavelet, the local statistics of each subband and the edge enhancement of the shape. The performance of the proposed method has been compared with that of the commonly novel approaches on both synthetic speckle images and real medical ultrasound images. The proposed method reveals superior performance in term of the PSNR value and perceptible quality. Because of the superior performance in noise reduction and edge preservation, the proposed method is more suitable than the other methods in computer-aided diagnosis.
基于双树小波的超声图像斑点去除和边缘增强算法
超声图像是疾病诊断的重要依据。不幸的是,由于散斑噪声,超声图像的质量通常受到限制。斑点去除是超声图像特征提取、分析和识别的重要预处理步骤。本文提出了一种超声图像增强方法。它利用了小波的可分性和多分辨率特性、各子带的局部统计特性和形状的边缘增强三种技术。将该方法在合成散斑图像和真实医学超声图像上的性能与常用的新方法进行了比较。该方法在PSNR值和感知质量方面表现出优异的性能。由于该方法具有较好的降噪和边缘保持性能,因此比其他方法更适合于计算机辅助诊断。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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