基于偏微分方程的医学超声图像降噪研究

Application of Partial Differential Equation in Medical Ultrasound Image Noise Reduction

提出一种将图像分解和几何分析相结合的算法去除超声图像中的斑点噪声。针对超声图像的斑点噪声为乘性噪声特性,将经典的ROF图像分解模型引入到适合于受乘性噪声污染的图像分解。超声图像经模型分解为轮廓部分、细节部分和噪声部分,然后对分解后的差值图像进行Ridgelet降噪,由于Ridgelet降噪克服传统小波分析方向性上的不敏感的缺点,能很好地保持图像边缘。处理后得到的图像无论是在斑点噪声去除、细节保护方面都优于传统的非线性滤波器和小波分析方法。实验表明,算法是完全可行和有效的。

The paper proposes a despeckling method combing image decomposition and ridgelet transformation denoising for removing speckle in ultrasound images. A speckle -contaminated image is splitted into a cartoon component and a component containing texture and noise. After that, ridgelet analysis is used to analyze the component containing texture and noise. Noise removal image is obtained by adding the cartoon component and the inverse - ridgelet transformation component. Simulation results indicate that the proposed method is better than other speckle removal filters, in terms of suppressing speckle and preserving image details. Experimental results reveal that this algorithm is completely feasible and effective.