Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland.
J Healthc Eng. 2017;2017:9271251. doi: 10.1155/2017/9271251. Epub 2017 Oct 8.
We propose a novel filtering technique capable of reducing the multiplicative noise in ultrasound images that is an extension of the denoising algorithms based on the concept of digital paths. In this approach, the filter weights are calculated taking into account the similarity between pixel intensities that belongs to the local neighborhood of the processed pixel, which is called a path. The output of the filter is estimated as the weighted average of pixels connected by the paths. The way of creating paths is pivotal and determines the effectiveness and computational complexity of the proposed filtering design. Such procedure can be effective for different types of noise but fail in the presence of multiplicative noise. To increase the filtering efficiency for this type of disturbances, we introduce some improvements of the basic concept and new classes of similarity functions and finally extend our techniques to a spatiotemporal domain. The experimental results prove that the proposed algorithm provides the comparable results with the state-of-the-art techniques for multiplicative noise removal in ultrasound images and it can be applied for real-time image enhancement of video streams.
我们提出了一种新颖的滤波技术，能够减少超声图像中的乘法噪声，这是基于数字路径概念的去噪算法的扩展。在这种方法中，滤波器权重的计算考虑了属于处理像素局部邻域的像素强度之间的相似性，这称为路径。滤波器的输出被估计为通过路径连接的像素的加权平均值。创建路径的方式是关键的，它决定了所提出的滤波设计的有效性和计算复杂性。这种方法对于不同类型的噪声可能是有效的，但在存在乘法噪声的情况下会失败。为了提高对这种干扰的滤波效率，我们引入了一些对基本概念的改进和新的相似性函数类，并最终将我们的技术扩展到时空域。实验结果证明，所提出的算法在去除超声图像中的乘法噪声方面可与最先进的技术相媲美，并且可应用于视频流的实时图像增强。
