Classification of Remote Sensing Image Based on Different Similarity Measures

被引：0

作者：

Shah, Kartik ^{[1
]}

Santoki, Shantanu ^{[1
]}

Ghetia, Himanshu ^{[1
]}

Aju, D. ^{[1
]}

机构：

[1] VIT Univ, Sch Comp Sci & Engn, Vellore 632014, Tamil Nadu, India

来源：

ARTIFICIAL INTELLIGENCE AND EVOLUTIONARY ALGORITHMS IN ENGINEERING SYSTEMS, VOL 1 | 2015年 / 324卷

关键词：

Unsupervised classification; Similarity measures; AWiFs image; ISODATA; TIME-SERIES; VEGETATION; MODIS; SEASONALITY;

D O I：

10.1007/978-81-322-2126-5_66

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Advanced wide field sensor (AWiFS) is a multi-spectral camera used to capture image from IRS-P6 (Indian remote sensing) satellite. Iterative self-organizing data analysis technique (ISODATA) is one of the most frequently used unsupervised classification algorithms. There are too many techniques available for classifying an image. In this paper, we will use similarity-based techniques to classify an image. Then, we will compare the result of each similarity measure classification techniques. We will use normalized difference vegetation index (NDVI) values to classify the images.

引用

页码：609 / 619

页数：11

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