基于Rician分布的散斑噪声的超声图像模拟算法*

为了衡量各种去噪算法的性能，在干净无噪声的图像上添加接近真实且可控的散斑噪声是非常重要的，提出一种基于Rician分布的不完全发育的斑点噪声的超声图像模拟算法。该算法考虑到了声波区域中包含孤立的强散射体的情况，同时结合了超声成像的扫描过程。以合成图像和肾脏图像为体模进行了模拟实验，并对最终生成的伪超声图像进行了噪声分布统计及拟合检验。实验结果表明该算法生成的伪超声图像在视觉上和理论上都接近真实的超声图像。

Ultrasound image simulation algorithm based on speckle noise based on Rician distribution

In order to measure the performance of various denoising algorithms, it is very important to add near-real and controllable speckle noise to clean and noise-free images, an ultrasonic image simulation algorithm of incompletely developed speckle noise based on Rician distribution is proposed. The algorithm takes into account the fact that there are isolated strong scatterers in the acoustic region, and combines with the ultrasound imaging scanning process. The synthetic image and the kidney image are used as phantoms for simulation experiments, and the noise distribution statistics and fitting tests are carried out on the final generated pseudo-ultrasound images. The experimental results show that the pseudo-ultrasound images generated by the algorithm are close to the real ultrasound images both visually and theoretically.