基于小波分析的CT图像噪声类型识别

基金项目:

广州科技支撑重点项目(2009Z1-E341)

详细信息

Identifying of Noise Types for Computed Tomography Images Based on Wavelet Analysis

School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China

摘要: 对CT图像噪声的类型进行识别,采用相适应的去噪方法提高图像去噪效果,减少去噪中的盲目性。分析小波高频子带系数的能量分布,利用直方图的信噪比和曲线拟合图的积分,对CT图像中最常见的两类噪声,即高斯噪声和椒盐噪声进行识别。直方图的信噪比R为0.2,曲线拟合图积分A为60,可作为高斯噪声和椒盐噪声分界线。对大量含噪CT图像的实验结果表明,该方法对CT图像噪声类型的识别比较准确。
- 小波分析 /
- 噪声类型 /
- 信噪比 /
- 面积
Abstract: To identify the noise types of CT image,corresponding method was used to improve the effect of image denoising,reduce the blindness.By analysis the energy distribution of the HH subband's coefficients in the wavelet domain,SNR of the histogram and area of curve fitting was used to distinguish Gaussian white noise and salt & pepper noise in computed tomography images.We found histogram of the signal to noise ratio R equals 0.2,curve fitting map area A equals 60 are the distinguish lines between Gaussian white noise and salt & pepper noise.The experiments on a wide variety of images show the veracity of this method in distinguishing noise.
- wavelet analysis /
- noise types /
- SNR /
- area