<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></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.

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

Department of Computer and Information Engineering

Department of Mathematics and Computer Science

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"X-ray image denoising based on wavelet transform and median filter"}

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...

Impulse (salt and pepper) noise	0.05	0.1	0.2	0.05	0.1	0.2
Gaussian white noise	0.01	0.01	0.01	0.02	0.02	0.02
Noise image	1562.134/16.0052	2442.991/14.0761	4312.669/11.6569	2142.309/14.6674	3026.395/13.2002	4744.419/11.2596
Median filtering algorithm	557.8286/20.4483	580.9237/20.2745	597.7874/20.1184	1031.996/17.8028	1061.468/17.6601	1061.973/17.6579
VisuShrink soft threshold method	265.7028/23.6036	356.5844/22.3437	575.4486/20.6593	283.8094/23.3212	369.1374/22.1506	515.6530/20.7221
Algorithm of this paper	144.3706/26.2155	145.5194/26.1817	160.3172/25.7669	212.1041/24.5683	215.3995/24.5023	227.1514/24.2748

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

Publié en ligne: 21 déc. 2020

Pages: 435 - 442

Reçu: 06 juin 2020

Accepté: 14 août 2020

DOI: https://doi.org/10.2478/amns.2020.2.00062

Mots clés
image denoising, median filter, wavelet transforms

© 2020 Hanlei Dong et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Fig. 2

Fig. 3

Experimental results of the denoising of the FEI image with mixed noise by different algorithms (MSE/PSNR).

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

Publié en ligne: 21 déc. 2020

Pages: 435 - 442

Reçu: 06 juin 2020

Accepté: 14 août 2020

DOI: https://doi.org/10.2478/amns.2020.2.00062

Mots clésimage denoising, median filter, wavelet transforms

© 2020 Hanlei Dong et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Fig. 2

Fig. 3

Experimental results of the denoising of the FEI image with mixed noise by different algorithms (MSE/PSNR).

Mots clés
image denoising, median filter, wavelet transforms