{"title":"高光谱相机图像去栅栏","authors":"Qi Zhang, Yuan Yuan, Xiaoqiang Lu","doi":"10.1109/CITS.2016.7546396","DOIUrl":null,"url":null,"abstract":"The main idea of image de-fencing refers to removing fence-like obstacles in the image and recovering the image. In this paper, rather than using a common RGB camera, we propose a novel image de-fencing algorithm with the help of a hyperspectral camera. Our algorithm consists of two phases: (1) automatically finding the location of the fence in the image, (2) image inpainting to reveal a fence-free image. With a hyperspectral camera, hundreds of images of the same scene under different wavelengths can be obtained instantly. By exploiting the spectral information of different positions in the scene with these hyperspectral images, the location of the fence can be distinguished from other objects. Then the fence can be removed and the image can be recovered with a novel image inpainting algorithm based on an approximate near-neighbor search method. Experiments demonstrate that our algorithm achieves considerable performance for the image de-fencing problem.","PeriodicalId":340958,"journal":{"name":"2016 International Conference on Computer, Information and Telecommunication Systems (CITS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Image de-fencing with hyperspectral camera\",\"authors\":\"Qi Zhang, Yuan Yuan, Xiaoqiang Lu\",\"doi\":\"10.1109/CITS.2016.7546396\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The main idea of image de-fencing refers to removing fence-like obstacles in the image and recovering the image. In this paper, rather than using a common RGB camera, we propose a novel image de-fencing algorithm with the help of a hyperspectral camera. Our algorithm consists of two phases: (1) automatically finding the location of the fence in the image, (2) image inpainting to reveal a fence-free image. With a hyperspectral camera, hundreds of images of the same scene under different wavelengths can be obtained instantly. By exploiting the spectral information of different positions in the scene with these hyperspectral images, the location of the fence can be distinguished from other objects. Then the fence can be removed and the image can be recovered with a novel image inpainting algorithm based on an approximate near-neighbor search method. Experiments demonstrate that our algorithm achieves considerable performance for the image de-fencing problem.\",\"PeriodicalId\":340958,\"journal\":{\"name\":\"2016 International Conference on Computer, Information and Telecommunication Systems (CITS)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-07-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Computer, Information and Telecommunication Systems (CITS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CITS.2016.7546396\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Computer, Information and Telecommunication Systems (CITS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CITS.2016.7546396","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The main idea of image de-fencing refers to removing fence-like obstacles in the image and recovering the image. In this paper, rather than using a common RGB camera, we propose a novel image de-fencing algorithm with the help of a hyperspectral camera. Our algorithm consists of two phases: (1) automatically finding the location of the fence in the image, (2) image inpainting to reveal a fence-free image. With a hyperspectral camera, hundreds of images of the same scene under different wavelengths can be obtained instantly. By exploiting the spectral information of different positions in the scene with these hyperspectral images, the location of the fence can be distinguished from other objects. Then the fence can be removed and the image can be recovered with a novel image inpainting algorithm based on an approximate near-neighbor search method. Experiments demonstrate that our algorithm achieves considerable performance for the image de-fencing problem.