K. Domínguez, M. M. Lavalle, Andrea Magadán Salazar y Gerardo Reyes Salgado
{"title":"Pulsed Neural Net plus Time Matrix for Bright Images Enhancement","authors":"K. Domínguez, M. M. Lavalle, Andrea Magadán Salazar y Gerardo Reyes Salgado","doi":"10.1109/ICMEAE.2019.00022","DOIUrl":null,"url":null,"abstract":"The digital images are widely used in diverse areas, these can be affected by diverse factors that affect its quality, which degrades its correct analysis. Bright images are an example of this, where the luminosity doesn’t allow the correct detection of different features for instance edges, textures and color, similarly, affect the human analysis. In this work a Third Generation Neuronal Network is implemented to enhancement bright images, specifically using the Intersection Cortical Model and a Time Matrix to modify the pixel value and obtain a better-quality image. The experiments shown that the proposed model is competitive to enhance bright images.","PeriodicalId":422872,"journal":{"name":"2019 International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMEAE.2019.00022","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
The digital images are widely used in diverse areas, these can be affected by diverse factors that affect its quality, which degrades its correct analysis. Bright images are an example of this, where the luminosity doesn’t allow the correct detection of different features for instance edges, textures and color, similarly, affect the human analysis. In this work a Third Generation Neuronal Network is implemented to enhancement bright images, specifically using the Intersection Cortical Model and a Time Matrix to modify the pixel value and obtain a better-quality image. The experiments shown that the proposed model is competitive to enhance bright images.