Biomedical Image and signal De-noising using Dual Tree Complex Wavelet Transform

摘要：

Dual tree complex wavelet transform(DTCWT) is a form of discrete wavelet transform, which generates complex coefficients by using a dual tree of wavelet filters to obtain their real and imaginary parts. The purposes of de-noising are reducing noise level and improving signal to noise ratio (SNR) without distorting the signal or image. This paper proposes a method for removing white Gaussian noise from ECG signals and biomedical images. The discrete wavelet transform (DWT) is very valuable in a large scope of de-noising problems. However, it has limitations such as oscillations of the coefficients at a singularity, lack of directional selectivity in higher dimensions, aliasing and consequent shift variance. The complex wavelet transform CWT strategy that we focus on in this paper is Kingsburys and Selesnicks dual tree CWT (DTCWT) which outperforms the critically decimated DWT in a range of applications, such as de-noising. Each complex wavelet is oriented along one of six possible directions, and the magnitude of each complex wavelet has a smooth bell-shape. In the final part of this paper, we present biomedical image and signal denoising by the means of thresholding magnitude of the wavelet coefficients.

关键词： de-noising CT noisy image noisy ECG dual tree complex wavelet

作者: F. Yousefi Rizi H. Ahmadi Noubari S. K. Setarehdan

作者单位: Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Eng., College of Engineering, University of Tehran Tehran, Iran

会议类型: 国际会议

会议名称: 2010 International Conference on Signal and Information Processing(2010年IEEE信号与信息处理国际会议 ICSIP2010)

会议地点: 长沙

会议语种:英文

页码: 409-412

在线出版日期: 2010-12-14（万方平台首次上网日期，不代表论文的发表时间）