文章基本信息

标题：A Framework to Classify the Satellite Images
本地全文：下载
作者：Manali Jain ; Amit Sinha
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2016
卷号：7
期号：1
页码：71-73
出版社：TechScience Publications
摘要：Satellite image classification uses the reflectancestatistics for individual pixels. Unsupervised and supervisedimage classification techniques are the two most commonapproaches. The user manually identifies each cluster withland cover classes. It’s often the case that multiple clustersrepresent a single land cover class. The user merges clustersinto a land cover type. In order to identify an object we musthave its features in the form of a feature vector. This can beachieved by feature extraction. There are various ways ofextracting features of an image. It can be based on color,texture or shape. Fuzzy inference system may also bedeveloped for classifying the satellite image. The use of gaborwavelet transform and use of SVM on satellite images toclassify the land into crop and non crop land are two betterways.
关键词：Gabor filter; SVM; Fuzzy Rules; supervised;classification.