{"title":"基于局部方向梯度的偏振图像去马赛克算法","authors":"Fei Xie, Jiajia Chen","doi":"10.1109/contesa52813.2021.9657154","DOIUrl":null,"url":null,"abstract":"A demosaicing algorithm based on local directional gradients for polarization image is presented. We use the pseudo-panchromatic image, which is calculated through the raw polarization image. During estimating the pseudo-panchromatic image, the directional gradient is used to preserve the details of it. Next, the interpolation algorithm based on the local directional gradient is performed to predict the missing values. Compared with the latest related methods, the proposed method reduces the root mean squared error by 62% and improves the structural similarity by 2%. Subjectively, we find that the degree and angle of linear polarization image produced by the proposed method have smaller errors and higher clarity.","PeriodicalId":323624,"journal":{"name":"2021 International Conference on Computing, Networking, Telecommunications & Engineering Sciences Applications (CoNTESA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Demosaicing Algorithm Based on Local Directional Gradients for Polarization Image\",\"authors\":\"Fei Xie, Jiajia Chen\",\"doi\":\"10.1109/contesa52813.2021.9657154\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A demosaicing algorithm based on local directional gradients for polarization image is presented. We use the pseudo-panchromatic image, which is calculated through the raw polarization image. During estimating the pseudo-panchromatic image, the directional gradient is used to preserve the details of it. Next, the interpolation algorithm based on the local directional gradient is performed to predict the missing values. Compared with the latest related methods, the proposed method reduces the root mean squared error by 62% and improves the structural similarity by 2%. Subjectively, we find that the degree and angle of linear polarization image produced by the proposed method have smaller errors and higher clarity.\",\"PeriodicalId\":323624,\"journal\":{\"name\":\"2021 International Conference on Computing, Networking, Telecommunications & Engineering Sciences Applications (CoNTESA)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Computing, Networking, Telecommunications & Engineering Sciences Applications (CoNTESA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/contesa52813.2021.9657154\",\"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 International Conference on Computing, Networking, Telecommunications & Engineering Sciences Applications (CoNTESA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/contesa52813.2021.9657154","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Demosaicing Algorithm Based on Local Directional Gradients for Polarization Image
A demosaicing algorithm based on local directional gradients for polarization image is presented. We use the pseudo-panchromatic image, which is calculated through the raw polarization image. During estimating the pseudo-panchromatic image, the directional gradient is used to preserve the details of it. Next, the interpolation algorithm based on the local directional gradient is performed to predict the missing values. Compared with the latest related methods, the proposed method reduces the root mean squared error by 62% and improves the structural similarity by 2%. Subjectively, we find that the degree and angle of linear polarization image produced by the proposed method have smaller errors and higher clarity.