{"title":"Integrating images and thermal signals with advanced algorithms","authors":"M. Lynnyk, Adrian Nakonechnyi","doi":"10.46299/j.isjea.20240303.02","DOIUrl":null,"url":null,"abstract":"This work considers possible approaches to improving the quality of image signal formation in both light and dark periods of the day, as well as reducing the impact of noise, interference, and artifacts on image signal characteristics. It is proposed to use the wavelet domain for the analysis of thermal and image signals with their subsequent possible complexation. The main features of the formation of such signals are indicated. It is shown that the proposed approach allows to improve the quality characteristics of image signals, especially in the dark period, as well as to ensure their effective processing related to filtering, compression, scaling and contrast change. A comparison of the obtained results of the proposed method with other existing similar signal processing approaches is given.","PeriodicalId":120311,"journal":{"name":"International Science Journal of Engineering & Agriculture","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Science Journal of Engineering & Agriculture","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46299/j.isjea.20240303.02","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This work considers possible approaches to improving the quality of image signal formation in both light and dark periods of the day, as well as reducing the impact of noise, interference, and artifacts on image signal characteristics. It is proposed to use the wavelet domain for the analysis of thermal and image signals with their subsequent possible complexation. The main features of the formation of such signals are indicated. It is shown that the proposed approach allows to improve the quality characteristics of image signals, especially in the dark period, as well as to ensure their effective processing related to filtering, compression, scaling and contrast change. A comparison of the obtained results of the proposed method with other existing similar signal processing approaches is given.