Multi-temporal Satellite Image Analysis Using Unsupervised Techniques

被引:0
作者
Arvind, C. S. [2 ]
Vanjare, Ashoka [3 ]
Omkar, S. N. [1 ]
Senthilnath, J. [3 ]
Mani, V. [3 ]
Diwakar, P. G. [1 ]
机构
[1] Indian Space Res Org, Earth Observat Syst, Bangalore 562140, Karnataka, India
[2] Telibrahma Convergent Commun Pvt Ltd, Bangalore, Karnataka, India
[3] Indian Inst Sci, Dept Aerosp Engn, Bangalore, Karnataka, India
来源
ADVANCES IN COMPUTING AND INFORMATION TECHNOLOGY, VOL 2 | 2013年 / 177卷
关键词
MODIS satellite images; unsupervised image segmentation techniques; performance evaluation indices;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents flood assessment using non-parametric techniques for multi-temporal time series MODES (Moderate Resolution Imaging Spectro radiometer) satellite images. The unsupervised methods like mean shift algorithm and median cut are used for automatic extraction of water pixel from the image. The extracted results presents a comparative study of unsupervised image segmentation methods. The performance evaluation indices like root mean square error and receiver operating characteristics are used to study algorithm performance. The result reported in this paper provides useful information for multi-temporal time series image analysis which can be used for current and future research.
引用
收藏
页码:757 / +
页数:3
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