{"title":"Matrix projection and its application in image processing","authors":"Xinyi Chen , Daizhan Cheng , Jun-e Feng","doi":"10.1016/j.dsp.2025.105231","DOIUrl":null,"url":null,"abstract":"<div><div>This paper proposes a new projection-based image compression and decompression (PC-PD) method for image processing. Inspired by Cheng projection processing vector, a novel matrix projection is introduced based on the matrix space structure and topological structure. Building on the matrix projection, the PC-PD method is developed to handle images. The effectiveness of the proposed method is demonstrated through experiments on gray and color images, as well as comparisons with other compressed sensing (CS) methods.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"163 ","pages":"Article 105231"},"PeriodicalIF":2.9000,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digital Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1051200425002532","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
This paper proposes a new projection-based image compression and decompression (PC-PD) method for image processing. Inspired by Cheng projection processing vector, a novel matrix projection is introduced based on the matrix space structure and topological structure. Building on the matrix projection, the PC-PD method is developed to handle images. The effectiveness of the proposed method is demonstrated through experiments on gray and color images, as well as comparisons with other compressed sensing (CS) methods.
期刊介绍:
Digital Signal Processing: A Review Journal is one of the oldest and most established journals in the field of signal processing yet it aims to be the most innovative. The Journal invites top quality research articles at the frontiers of research in all aspects of signal processing. Our objective is to provide a platform for the publication of ground-breaking research in signal processing with both academic and industrial appeal.
The journal has a special emphasis on statistical signal processing methodology such as Bayesian signal processing, and encourages articles on emerging applications of signal processing such as:
• big data• machine learning• internet of things• information security• systems biology and computational biology,• financial time series analysis,• autonomous vehicles,• quantum computing,• neuromorphic engineering,• human-computer interaction and intelligent user interfaces,• environmental signal processing,• geophysical signal processing including seismic signal processing,• chemioinformatics and bioinformatics,• audio, visual and performance arts,• disaster management and prevention,• renewable energy,