{"title":"像素纹理指数算法及其应用","authors":"Xiaodan Sun, Xiaofang Sun","doi":"10.14358/pers.23-00051r2","DOIUrl":null,"url":null,"abstract":"Image segmentation is essential for object-oriented analysis, and classification is a critical parameter influencing analysis accuracy. However, image classification and segmentation based on spectral features are easily perturbed by the high-frequency information of a high spatial\n resolution remotely sensed (HSRRS) image, degrading its classification and segmentation quality. This article first presents a pixel texture index (PTI) by describing the texture and edge in a local area surrounding a pixel. Indeed.. The experimental results highlight that the HSRRS image\n classification and segmentation quality can be effectively improved by combining it with the PTI image. Indeed, the overall accuracy improved from 7% to 14%, and the kappa can be increased from 11% to 24%, respectively.","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":"6 25","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Pixel Texture Index Algorithm and Its Application\",\"authors\":\"Xiaodan Sun, Xiaofang Sun\",\"doi\":\"10.14358/pers.23-00051r2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Image segmentation is essential for object-oriented analysis, and classification is a critical parameter influencing analysis accuracy. However, image classification and segmentation based on spectral features are easily perturbed by the high-frequency information of a high spatial\\n resolution remotely sensed (HSRRS) image, degrading its classification and segmentation quality. This article first presents a pixel texture index (PTI) by describing the texture and edge in a local area surrounding a pixel. Indeed.. The experimental results highlight that the HSRRS image\\n classification and segmentation quality can be effectively improved by combining it with the PTI image. Indeed, the overall accuracy improved from 7% to 14%, and the kappa can be increased from 11% to 24%, respectively.\",\"PeriodicalId\":211256,\"journal\":{\"name\":\"Photogrammetric Engineering & Remote Sensing\",\"volume\":\"6 25\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Photogrammetric Engineering & Remote Sensing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14358/pers.23-00051r2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Photogrammetric Engineering & Remote Sensing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14358/pers.23-00051r2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Pixel Texture Index Algorithm and Its Application
Image segmentation is essential for object-oriented analysis, and classification is a critical parameter influencing analysis accuracy. However, image classification and segmentation based on spectral features are easily perturbed by the high-frequency information of a high spatial
resolution remotely sensed (HSRRS) image, degrading its classification and segmentation quality. This article first presents a pixel texture index (PTI) by describing the texture and edge in a local area surrounding a pixel. Indeed.. The experimental results highlight that the HSRRS image
classification and segmentation quality can be effectively improved by combining it with the PTI image. Indeed, the overall accuracy improved from 7% to 14%, and the kappa can be increased from 11% to 24%, respectively.