Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 2


Published
on

October 28, 2023


Pages


DOI

Article

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

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Authors

Li Wang Affiliation:
Department of Electronic Information Engineering, Nanchong Vocational and Technical College, Nanchong, Sichuan, 637131, China.
, Hongping Wang Affiliation:
Department of Electronic Information Engineering, Nanchong Vocational and Technical College, Nanchong, Sichuan, 637131, China.
, Sanshan He Affiliation:
Network and Information Management Center of Nanchong Vocational and Technical College, Nanchong, Sichuan, 637131, China.
and Hua Yang Affiliation:
Department of Electronic Information Engineering, Nanchong Vocational and Technical College, Nanchong, Sichuan, 637131, China.


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.


Keywords

Nyquist sampling, Compressive perception theory, Optimal wavelet packet basis, Image sparse representation, Image analysis, 97P25


Citation

Wang, L., Wang, H., He, S., & Yang, H. (2023). Research on image analysis and processing method based on compressed perception technology. Applied Mathematics and Nonlinear Sciences, 8(2). https://doi.org/10.2478/amns.2023.2.00847

Published by: Engineering Journals

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