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

<p>In physics class, the residual data before and after noise elimination contains more image information. In the equivalent wave domain, the K-SVD method is used to eliminate noise in the noise image of each frequency band and the residual of each frequency band. The main objective is to improve the image quality of noise. The method is combined with the denoised sub-spectrum to obtain the denoised sub-spectrum with the residual signal. An inverse isomorphic wave is used for noise reduction. The simulation results show that the noise reduction algorithm using K-SVD is better than the equivalent waveform and K-SVD mode. This method has achieved good results in practical application.</p>
</abstract>

In physics class, the residual data before and after noise elimination contains more image information. In the equivalent wave domain, the K-SVD method is used to eliminate noise in the noise image of each frequency band and the residual of each frequency band. The main objective is to improve the image quality of noise. The method is combined with the denoised sub-spectrum to obtain the denoised sub-spectrum with the residual signal. An inverse isomorphic wave is used for noise reduction. The simulation results show that the noise reduction algorithm using K-SVD is better than the equivalent waveform and K-SVD mode. This method has achieved good results in practical application.

Improved K-SVD Model in Higher Vocational Physics Teaching

Applied Mathematics and Nonlinear Sciences

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

{"article-title":"Improved K-SVD Model in Higher Vocational Physics Teaching"}

In physics class, the residual data before and after noise elimination contains more image information. In the equivalent wave domain, the K-SVD method is used...

Improved K-SVD Model in Higher Vocational Physics Teaching

Pubblicato online: 22 giu 2023

Pagine: 2627 - 2634

Ricevuto: 08 lug 2022

Accettato: 30 dic 2022

DOI: https://doi.org/10.2478/amns.2023.1.00443

Parole chiave
Higher vocational physics teaching, Image denoising, Image residual information, Contour wave transform, K-SVD noise reduction model

© 2023 Shuai Yang, published by Sciendo

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

Improved K-SVD Model in Higher Vocational Physics Teaching

Pubblicato online: 22 giu 2023

Pagine: 2627 - 2634

Ricevuto: 08 lug 2022

Accettato: 30 dic 2022

DOI: https://doi.org/10.2478/amns.2023.1.00443

Parole chiaveHigher vocational physics teaching, Image denoising, Image residual information, Contour wave transform, K-SVD noise reduction model

© 2023 Shuai Yang, published by Sciendo

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

Parole chiave
Higher vocational physics teaching, Image denoising, Image residual information, Contour wave transform, K-SVD noise reduction model