{"title":"基于深度学习的单幅图像超分辨率增强算法研究","authors":"Ming Han, Han Liu","doi":"10.1109/PHM-Nanjing52125.2021.9612927","DOIUrl":null,"url":null,"abstract":"To solve the problem of low edge protection index in traditional enhancement algorithm, a single image super-resolution enhancement algorithm based on deep learning is proposed. The super-resolution feature of a single image is extracted by the sinusoidal two-dimensional transform function modulated by Gaussian function. The local Laplacian filter is used to preprocess the super-resolution of a single image, and the deep learning method is introduced to enhance the super-resolution of a single image. The experimental results show that the improved method has higher edge protection index, can effectively improve the enhancement accuracy, and has certain advantages.","PeriodicalId":436428,"journal":{"name":"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on single image super resolution enhancement algorithm based on deep learning\",\"authors\":\"Ming Han, Han Liu\",\"doi\":\"10.1109/PHM-Nanjing52125.2021.9612927\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To solve the problem of low edge protection index in traditional enhancement algorithm, a single image super-resolution enhancement algorithm based on deep learning is proposed. The super-resolution feature of a single image is extracted by the sinusoidal two-dimensional transform function modulated by Gaussian function. The local Laplacian filter is used to preprocess the super-resolution of a single image, and the deep learning method is introduced to enhance the super-resolution of a single image. The experimental results show that the improved method has higher edge protection index, can effectively improve the enhancement accuracy, and has certain advantages.\",\"PeriodicalId\":436428,\"journal\":{\"name\":\"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PHM-Nanjing52125.2021.9612927\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PHM-Nanjing52125.2021.9612927","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on single image super resolution enhancement algorithm based on deep learning
To solve the problem of low edge protection index in traditional enhancement algorithm, a single image super-resolution enhancement algorithm based on deep learning is proposed. The super-resolution feature of a single image is extracted by the sinusoidal two-dimensional transform function modulated by Gaussian function. The local Laplacian filter is used to preprocess the super-resolution of a single image, and the deep learning method is introduced to enhance the super-resolution of a single image. The experimental results show that the improved method has higher edge protection index, can effectively improve the enhancement accuracy, and has certain advantages.