{"title":"Color and wavelet based identification of urban and agricultural area using texture features in satellite images","authors":"M. Umaselvi, S. S. Kumar, M. Athithya","doi":"10.1109/ICGHPC.2013.6533914","DOIUrl":null,"url":null,"abstract":"This paper represents unsupervised method of color based segmentation using clustering to classify vegetated and urban area in Satellite images. Now a day due to the progresses in spatial resolution of satellite imagery, the methods of segment-based image analysis for generating and updating geographical information are becoming more important. In this work, one method proposed a segmentation of various clusters by La*b* color space and Texture Feature was analyzed. The Second method proposed a segmentation of image by wavelet and Texture Feature was analyzed. Algorithm is verified for simulated images and applied for a selected satellite image processing.","PeriodicalId":119498,"journal":{"name":"2013 International Conference on Green High Performance Computing (ICGHPC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Green High Performance Computing (ICGHPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICGHPC.2013.6533914","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper represents unsupervised method of color based segmentation using clustering to classify vegetated and urban area in Satellite images. Now a day due to the progresses in spatial resolution of satellite imagery, the methods of segment-based image analysis for generating and updating geographical information are becoming more important. In this work, one method proposed a segmentation of various clusters by La*b* color space and Texture Feature was analyzed. The Second method proposed a segmentation of image by wavelet and Texture Feature was analyzed. Algorithm is verified for simulated images and applied for a selected satellite image processing.