基于幂次变换的自适应超声医学图像去噪算法

A Self-Adaptive De-Noising Algorithm of Medical Ultrasound Image Based on Power Transformation

目的探求一种有效地去除噪声又能很好地保留超声医学图像高频细节信息的去噪算法。方法提出一种基于幂次变换的自适应超声医学图像去噪算法,该算法主要是对大于阈值的小波系数进行幂次变换,使处理后的小波系数尽可能地接近原始小波系数,并能很好地保留小波系数的连续性。结果实验结果表明,噪声较小时,该算法方差较小,并且视觉效果优于软阈值算法。结论该算法有效地实现了对超声医学图像斑点噪声的自适应抑制,在噪声较小时,能很好地去除噪声,并保留高频细节信息。

Objective To explore a de-noising algorithm which can effectively reduce noise and be very good retention highfrequency detail of medical ultrasonic image.Methods An adaptive ultrasonic medical image denoising algorithm based on power transformation was proposed,which was mainly used to transform the power of wavelet coefficients larger than the threshold value,so that the processed wavelet coefficients could be as close as possible to the original wavelet coefficients,and the continuity of wavelet coefficients could be well preserved.Results The experimental results showed that the power transformation outperformed the soft-threshold algorithm in root mean square error(RMSE)and vision effect when the noises variances were small.Conclusion This algorithm effectively realizes adaptive suppression of speckle noise in ultrasonic medical image.When the noise is small,it can remove the noise well and retain the high frequency detail information.