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

<p>This paper analyzes the traditional Shannon-Nyquist sampling theorem, introduces the process of compressive perception theory and the key techniques of compressive perception in image sparse representation, design of measurement matrix and signal reconstruction, and explores the application of compressive perception in the field of image analysis and processing. Meanwhile, the image system imaging is constructed based on the compressive perception technique, and the process of wavelet packet subspace decomposition and reconstruction constructs the compressive perception image algorithm based on the optimal wavelet packet basis. The algorithm simulation results show that the minimum signal entropy is 16*4 in the minimum wavelet chunking way, at which the minimum values are -0.35, -0.04, -0.07, and -0.01, respectively.</p>
</abstract>

This paper analyzes the traditional Shannon-Nyquist sampling theorem, introduces the process of compressive perception theory and the key techniques of compressive perception in image sparse representation, design of measurement matrix and signal reconstruction, and explores the application of compressive perception in the field of image analysis and processing. Meanwhile, the image system imaging is constructed based on the compressive perception technique, and the process of wavelet packet subspace decomposition and reconstruction constructs the compressive perception image algorithm based on the optimal wavelet packet basis. The algorithm simulation results show that the minimum signal entropy is 16*4 in the minimum wavelet chunking way, at which the minimum values are -0.35, -0.04, -0.07, and -0.01, respectively.

Research on image analysis and processing method based on compressed perception technology

Department of Electronic Information Engineering

Applied Mathematics and Nonlinear Sciences

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

This paper analyzes the traditional Shannon-Nyquist sampling theorem, introduces the process of compressive perception theory and the key techniques of...

Research on image analysis and processing method based on compressed perception technology

Pubblicato online: 28 ott 2023

Pagine: -

Ricevuto: 21 gen 2023

Accettato: 08 mag 2023

DOI: https://doi.org/10.2478/amns.2023.2.00847

Parole chiave
Nyquist sampling, Compressive perception theory, Optimal wavelet packet basis, Image sparse representation, Image analysis

© 2023 Li Wang et al., published by Sciendo

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

Research on image analysis and processing method based on compressed perception technology

Pubblicato online: 28 ott 2023

Pagine: -

Ricevuto: 21 gen 2023

Accettato: 08 mag 2023

DOI: https://doi.org/10.2478/amns.2023.2.00847

Parole chiaveNyquist sampling, Compressive perception theory, Optimal wavelet packet basis, Image sparse representation, Image analysis

© 2023 Li Wang et al., published by Sciendo

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

Parole chiave
Nyquist sampling, Compressive perception theory, Optimal wavelet packet basis, Image sparse representation, Image analysis