Unsupervised Classification based on Decomposition of RISAT-1 Images for oil spill detection

被引：0
|
作者：
Kumar, Lingenahalli Jayadev Vijaya [1 ]
Kishore, J. K. [2 ]
Rao, P. Kesava [3 ]
机构：
[1] ISRO, Master Control Facil, Hassan, Karnataka, India
[2] ISRO Satellite Ctr, Bangalore, Karnataka, India
[3] IARE, Natl Remote Sensing Ctr, Hyderabad, Andhra Pradesh, India
来源：
2013 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI) | 2013年
关键词：
SAR; RISAT-1; Oil Spill;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The main aim of this paper is to discuss the identification of oil spill using Hybrid polarity SAR architecture of India's first Radar imaging Satellite RISAT-1 SAR images. The RISAT-1's Hybrid polarity SAR architecture and imaging modes are discussed. The characterization of EM waves with polarization ellipse and polarization state are discussed. The Stokes parameters S1, S2, S3, S4 and its importance for deriving ellipticity and relative phase angle is described. The new m-chi and m-delta decomposition methods are used in India's Chandrayaan-1 mission for water-ice identification are illustrated. These methods are applied to Norway oil spill image of RISAT-1 to identify the oil spill region and discriminate look alikes. The preliminary results are encouraging to highlight the potential of unsupervised classification for identification of oil spill with SAR images
引用
收藏
页码：739 / 746
页数：8
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