{"title":"使用图像质量度量评估RGB和HSV色彩空间的卫星图像分割","authors":"P. Ganesan, V. Rajini","doi":"10.1109/ICAEE.2014.6838441","DOIUrl":null,"url":null,"abstract":"This paper presents a comparative study of the segmentation of satellite images in RGB and HSV color space using modified fuzzy c means clustering algorithm. The segmented images are compared with the original input images by using number of bivariate image quality parameters. These parameters measure the similarity between the input and the segmented image on the basis of comparing the corresponding pixels of the two images and present a numerical value as a result. The experiments are performed on GeoEye-1 satellite images to test the efficiency and robustness of the proposed method.","PeriodicalId":151739,"journal":{"name":"2014 International Conference on Advances in Electrical Engineering (ICAEE)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"57","resultStr":"{\"title\":\"Assessment of satellite image segmentation in RGB and HSV color space using image quality measures\",\"authors\":\"P. Ganesan, V. Rajini\",\"doi\":\"10.1109/ICAEE.2014.6838441\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a comparative study of the segmentation of satellite images in RGB and HSV color space using modified fuzzy c means clustering algorithm. The segmented images are compared with the original input images by using number of bivariate image quality parameters. These parameters measure the similarity between the input and the segmented image on the basis of comparing the corresponding pixels of the two images and present a numerical value as a result. The experiments are performed on GeoEye-1 satellite images to test the efficiency and robustness of the proposed method.\",\"PeriodicalId\":151739,\"journal\":{\"name\":\"2014 International Conference on Advances in Electrical Engineering (ICAEE)\",\"volume\":\"77 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"57\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Advances in Electrical Engineering (ICAEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAEE.2014.6838441\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Advances in Electrical Engineering (ICAEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAEE.2014.6838441","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Assessment of satellite image segmentation in RGB and HSV color space using image quality measures
This paper presents a comparative study of the segmentation of satellite images in RGB and HSV color space using modified fuzzy c means clustering algorithm. The segmented images are compared with the original input images by using number of bivariate image quality parameters. These parameters measure the similarity between the input and the segmented image on the basis of comparing the corresponding pixels of the two images and present a numerical value as a result. The experiments are performed on GeoEye-1 satellite images to test the efficiency and robustness of the proposed method.