基于颜色和小波的卫星图像纹理特征的城乡区域识别

M. Umaselvi, S. S. Kumar, M. Athithya
{"title":"基于颜色和小波的卫星图像纹理特征的城乡区域识别","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":"{\"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}","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

摘要

提出了一种基于颜色的无监督聚类分割方法,对卫星图像中的植被和城市区域进行分类。随着卫星图像空间分辨率的不断提高,基于图像分段分析的地理信息生成和更新方法变得越来越重要。本文分析了一种利用La*b*颜色空间和纹理特征对不同聚类进行分割的方法。提出了一种基于小波和纹理特征的图像分割方法。对仿真图像进行了验证,并将算法应用于选定的卫星图像处理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Color and wavelet based identification of urban and agricultural area using texture features in satellite images
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信