CT image denoising based on locally adaptive thresholding


  • Miroslav Petrov The Department of Computer Systems and Technologies of the Faculty of Mathematics and Informatics of the St. Cyril and St. Methodius University of Veliko Turnovo, Veliko Turnovo, Bulgaria




repagular wavelet transform, statistical noise reduction, x-ray computed tomography


The noise in reconstructed X-ray Computed Tomography (CT) slices is complex, non-stationary and indefinitely distributed. Subsequent image processing is needed in order to achieve a good-quality medical diagnosis. It requires a sufficiently great ratio between the detailed contrasts and the noise component amplitude. This paper presents an adaptive method for noise reduction in CT images, based on the local statistical evaluation of the noise component in the domain of Repagular Wavelet Transformation (RWT). Considering the spatial dependence of the noise strength, the threshold constant for processing the high frequency coefficients in the proposed shrinkage method is a function of the local standard deviation of the noise for each pixel of the image. Experimental studies have been conducted using different images in order to evaluate the effectiveness of the proposed algorithm.

Author Biography

Miroslav Petrov, The Department of Computer Systems and Technologies of the Faculty of Mathematics and Informatics of the St. Cyril and St. Methodius University of Veliko Turnovo, Veliko Turnovo

Miroslav Petrov,

Ph.D., an assistant professor at the Department of Computer Systems and Technologies of the Faculty of Mathematics and Informatics of the St. Cyril and St. Methodius University of Veliko Turnovo, Veliko Turnovo, Bulgaria.

He received BS and MS degrees in Communications and Security Technologies and Systems at the Technical University of Varna in 1994 and 1999. He was awarded his PhD degree - "Automated systems for Information Processing and Management" at the Technical University of Sofia in 2014.

His current research interests include Computer Vision, Image Processing, Communication and Computer Systems.


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