B. Stojanovic, Snezana Puzović, Nataša Vlahović, Ranko Petrović, Srđan Stanković
{"title":"实时多传感器红外图像增强","authors":"B. Stojanovic, Snezana Puzović, Nataša Vlahović, Ranko Petrović, Srđan Stanković","doi":"10.1109/NEUREL.2018.8587023","DOIUrl":null,"url":null,"abstract":"Video enhancement algorithms in long-range multi-sensor surveillance systems are of great importance. Infrared sensors typically suffer from blur and noise originating from sensors and their environment. This paper proposes a real-time infrared imaging enhancement algorithm, applicable to multiple sensor types. The research presented in this paper is introductory for developing smart, adaptive, machine learning based enhancement systems.","PeriodicalId":371831,"journal":{"name":"2018 14th Symposium on Neural Networks and Applications (NEUREL)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Real-Time Multi-Sensor Infrared Imagery Enhancement\",\"authors\":\"B. Stojanovic, Snezana Puzović, Nataša Vlahović, Ranko Petrović, Srđan Stanković\",\"doi\":\"10.1109/NEUREL.2018.8587023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Video enhancement algorithms in long-range multi-sensor surveillance systems are of great importance. Infrared sensors typically suffer from blur and noise originating from sensors and their environment. This paper proposes a real-time infrared imaging enhancement algorithm, applicable to multiple sensor types. The research presented in this paper is introductory for developing smart, adaptive, machine learning based enhancement systems.\",\"PeriodicalId\":371831,\"journal\":{\"name\":\"2018 14th Symposium on Neural Networks and Applications (NEUREL)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 14th Symposium on Neural Networks and Applications (NEUREL)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NEUREL.2018.8587023\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 14th Symposium on Neural Networks and Applications (NEUREL)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NEUREL.2018.8587023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Video enhancement algorithms in long-range multi-sensor surveillance systems are of great importance. Infrared sensors typically suffer from blur and noise originating from sensors and their environment. This paper proposes a real-time infrared imaging enhancement algorithm, applicable to multiple sensor types. The research presented in this paper is introductory for developing smart, adaptive, machine learning based enhancement systems.
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