基于改进NL-Means的医学CT图像降噪

Base on Improved NL-Means Algorithm for Medical CT Image Denoising

摘要: 医学CT图像在成像的过程中,不可避免地会引入噪声。图像噪声会降低图像质量,影响临床诊断。因此,医学CT图像降噪在诊疗中起着重要作用。本文首先介绍了经典的NL-Means(非局部均值算法)算法,然后在此基础上改变对降噪起关键作用的加权核函数。实验证明本文算法对医学图像降噪有一定的效果,并且能够更好保留原图像的细节信息。在图像降噪后的峰值信噪比(PSNR)方面,本文算法比NL-Means算法最大可提升2.59 dB。

Abstract: The medical CT Image will bring in noise when in the process of imaging. The noise can reduce the quality of image and affect the clinical diagnosis. Therefore, medical CT image denoising plays an important role in the diagnosis and treatment. This paper proposes the classical NL-Means algorithm at firse, then changes the denoising key role of the weighted kernel function. The experiment shows the algorithm for medical CT image denoising have certain effect, and can better preserve the detail information. For the PSNR, it can be improved by 2.59 dB at most.