计算机工程与应用 ›› 2012, Vol. 48 ›› Issue (6): 190-192.

• 图形、图像、模式识别 • 上一篇    下一篇

Lipschitz指数与平稳小波变换在CT图像去噪中的应用

杨 勇1,郭吉强2   

  1. 1.重庆科创职业学院 机械与电子工程学院,重庆 402160
    2.重庆大学 光电工程学院,重庆 400044
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2012-02-21 发布日期:2012-02-21

Application of Lipschitz exponent and SWT for denoising of CT image

YANG Yong1, GUO Jiqiang2   

  1. 1.School of Mechanical and Electronic Engineering, Chongqing Creation Vocational College, Chongqing 402160, China
    2.College of Optoelectronic Engineering, Chongqing University, Chongqing 400044, China
  • Received:1900-01-01 Revised:1900-01-01 Online:2012-02-21 Published:2012-02-21

摘要: 针对CT切片图像噪声特点以及应用需求,提出了基于Lipschitz指数和平稳小波的CT图像去噪算法。利用改进的中值滤波器滤除图像的脉冲噪声,然后根据图像阶梯边缘的Lipschitz指数与小波系数之间的关系,在更好地保护图像边缘细节的前提下,利用平稳小波变换的阈值去噪方法滤除高斯噪声。实验结果表明,该方法无论是在视觉效果上,还是在最小均方差意义和信噪比增益上,以及保护图像边缘细节上都有很大提高。

Abstract: According to the noise characteristic and application requirement of Computed Tomography(CT) slice image, the denoising algorithm based on Lipschitz exponent and Stationary Wavelet Transform(SWT) is proposed. This algorithm uses the improved median filter for filtering the impulse noise, then based on the relationship of Lipschitz exponent of step edge and wavelet coefficient and under the premise of protecting the image edge details, the threshold denoising method based on SWT for filtering Gaussian noise is adopted. The experimental results show that whether the visual effects or the perfomance of the minimum Mean Square Error(MSE) and the Peak of Signal-to-Noise Ratio(PSNR), and protecting the image edge details of this algorithm have great improvement.