CT image noise reduction based on adaptive wiener filtering with Wavelet packet thresholding

Computed Tomography (CT) is streamlined in radiological diagnostics and has become an imperative tool in medical examinations. The difficulty that arises with the demand is to improve CT image quality without increasing dose. In this paper, Wavelet based noise reduction technique is proposed to improve image quality where adaptive Wiener filtering and Wavelet Packet Threshold (WPT) algorithm are applied. The Noisy CT image is decomposed using DWT, where approximation part is filtered using WPT algorithm and detail part is filtered by the adaptive Wiener filtering. By using the level dependent, the wavelet packet tree coefficients are calculated using optimal linear interpolation shrinkage function. Denoised image is acquired using wavelet packet reconstruction and inverse DWT. The value of the peak signal to noise ratio (PSNR) is used as the measure of image visual quality. Experimental results demonstrate that the proposed method improves the image visual quality in respect of noise removal and edge preservation.

[1]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Karim Faez,et al.  A new wavelet-based fuzzy single and multi-channel image denoising , 2010, Image Vis. Comput..

[3]  Bülent Sankur,et al.  Survey over image thresholding techniques and quantitative performance evaluation , 2004, J. Electronic Imaging.

[4]  D. L. Donoho,et al.  Ideal spacial adaptation via wavelet shrinkage , 1994 .

[5]  P. Shui,et al.  Image denoising algorithm via best wavelet packet base using Wiener cost function , 2007 .

[6]  Martin Vetterli,et al.  Adaptive wavelet thresholding for image denoising and compression , 2000, IEEE Trans. Image Process..

[7]  Yunhong Li,et al.  Wavelet Packet Denoising Algorithm Based on Correctional Wiener Filtering , 2013 .

[8]  Li Ke,et al.  Multiscale Wiener filtering method for low-dose CT images , 2010, 2010 3rd International Conference on Biomedical Engineering and Informatics.

[9]  Rainer Raupach,et al.  Analytic noise propagation for anisotropic denoising of CT images , 2008, 2008 IEEE Nuclear Science Symposium Conference Record.

[10]  Hossein Nezamabadi-pour,et al.  Image denoising in the wavelet domain using a new adaptive thresholding function , 2009, Neurocomputing.

[11]  M. Kalra,et al.  Strategies for CT radiation dose optimization. , 2004, Radiology.

[12]  Ahmad Reza Naghsh-Nilchi,et al.  Efficient Image Denoising Method Based on a New Adaptive Wavelet Packet Thresholding Function , 2012, IEEE Transactions on Image Processing.

[13]  Jay Wu,et al.  Noise reduction of low-dose computed tomography using the multi-resolution total variation minimization algorithm , 2013, Medical Imaging.