【摘要】 针对医学超声图像上的斑点噪声,本文提出一种基于自适应形态滤波的降噪方法。首先构造一组检测图像中不同像素值突变的结构因子;再对每个结构因子构造相应的形态滤波结构元;最后对每个像素点邻域进行结构检测,找到该点处最可能存在的突变结构,以相应的结构元完成该点的形态滤波。对不同信噪比的仿真图像和实际图像分别采用本文方法和各向异性扩散滤波、不同尺度传统形态滤波进行了比较实验,结果表明:采用本方法可将超声图像的信噪比、对比度噪声比和图像优度分别平均提高15%、37%和69%,优于其它方法。更多还原

【Abstract】 In view of speckle noise in medical ultrasound image, a denosing method based on adaptive morphological filter was proposed. Firstly, a set of structuring factors was constructed to detect different sudden changes of pixel values in images. Then a corresponding structuring element for morphological filtering was established for each structuring factor. Finally, the most possible structures of sudden changes in each pixel’s neighborhood were detected by using the set of structuring factors and a morphological filtering was performed to the pixel with the corresponding structuring element. The comparison experiment was carried out on simulated and real ultrasound images by using the proposed method, the speckle reducing anisotropic diffusion and different scale morphological filters, respectively. It is shown that the proposed method averagely improves the Signal-to-noise Ratio (SNR), Contrast-to-noise Ratio (CNR) and Figure of Merit (FOM) of ultrasound images by 15%, 37% and 69%. Therefore, the adaptive morphological despeckling filter may be an effective method to suppress speckle in ultrasound images.更多还原