{"title":"目的建立遥感影像质量评价的全参考影像评价指标","authors":"R. Maruthi, P. Anusha, P. Sankar, K. Thiyagaragan","doi":"10.1109/ICEEICT56924.2023.10157402","DOIUrl":null,"url":null,"abstract":"Image Quality (IQ) assessment is a very complex task and it is extremely important to evaluate the images with the metrics. The metrics applied can be a full reference, partial reference or no-reference metric and it depends on the application and availability of the ground truth. Most of the IQ metrics are developed by considering the Visual System (VS) of humans. The assessment methods studied in this paper focuses on some of the Full-Reference (FR) measures and it is used to estimate the remote sensing noisy images. The effectiveness of the measures demonstrates a considerable outcome and demonstrates how well the noisy remote sensing images are being quantified.","PeriodicalId":345324,"journal":{"name":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Objective Full-Reference Image Assessment Metrics for Estimating the Quality of Remote Sensing Images\",\"authors\":\"R. Maruthi, P. Anusha, P. Sankar, K. Thiyagaragan\",\"doi\":\"10.1109/ICEEICT56924.2023.10157402\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Image Quality (IQ) assessment is a very complex task and it is extremely important to evaluate the images with the metrics. The metrics applied can be a full reference, partial reference or no-reference metric and it depends on the application and availability of the ground truth. Most of the IQ metrics are developed by considering the Visual System (VS) of humans. The assessment methods studied in this paper focuses on some of the Full-Reference (FR) measures and it is used to estimate the remote sensing noisy images. The effectiveness of the measures demonstrates a considerable outcome and demonstrates how well the noisy remote sensing images are being quantified.\",\"PeriodicalId\":345324,\"journal\":{\"name\":\"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEEICT56924.2023.10157402\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEEICT56924.2023.10157402","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Objective Full-Reference Image Assessment Metrics for Estimating the Quality of Remote Sensing Images
Image Quality (IQ) assessment is a very complex task and it is extremely important to evaluate the images with the metrics. The metrics applied can be a full reference, partial reference or no-reference metric and it depends on the application and availability of the ground truth. Most of the IQ metrics are developed by considering the Visual System (VS) of humans. The assessment methods studied in this paper focuses on some of the Full-Reference (FR) measures and it is used to estimate the remote sensing noisy images. The effectiveness of the measures demonstrates a considerable outcome and demonstrates how well the noisy remote sensing images are being quantified.