Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 5, Issue 2


Published
on

December 21, 2020


Pages

435-442


DOI

Article

X-ray image denoising based on wavelet transform and median filter

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Authors

Hanlei Dong Affiliation:
Department of Computer and Information Engineering, Luoyang Institute of Science and Technology, Luoyang 471023, China
, Liguo Zhao Affiliation:
Department of Computer and Information Engineering, Luoyang Institute of Science and Technology, Luoyang 471023, China
, Yunxing Shu Affiliation:
Department of Computer and Information Engineering, Luoyang Institute of Science and Technology, Luoyang 471023, China
and Neal N. Xiong Affiliation:
Department of Mathematics and Computer Science, Northeastern State University, USA


Abstract

This paper mainly proposed and researched based on wavelet transform, and then used the X-map denoising technique of value filter. In other words, the value image was filtered in the spatial domain, and the value filtering was used as the standard pulse (salt) noise, also used as in the wavelet domain. After the filtered image was decomposed by biorthogonal double wavelet transform, a wavelet coefficient matrix was generated, and a soft threshold quantisation process was performed on the wavelet coefficients to produce a new wavelet coefficient matrix. In the end, they used a new wavelet coefficient matrix for image reconstruction. The processing resulted that the denoising method proposed in this paper showed that the X image can be denoised, which not only reduced the X-picture-like noise but also preserved the X-picture-like details as much as possible. It also helped to enhance diagnostic accuracy and reduced the difference in reading.


Keywords

image denoising, median filter, wavelet transforms, S12503, 94A08, 94A12


Citation

Dong, H., Zhao, L., Shu, Y., & Xiong, N. N. (2020). X-ray image denoising based on wavelet transform and median filter. Applied Mathematics and Nonlinear Sciences, 5(2), 435–442. https://doi.org/10.2478/amns.2020.2.00062

Published by: Engineering Journals

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