Open AccessA review of remotely sensed satellite image classification
Author(s) -
Sakshi Dhingra,
Dharminder Kumar
Publication year - 2019
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v9i3.pp1720-1731
Subject(s) - computer science , contextual image classification , satellite image , satellite , land cover , feature extraction , remote sensing , field (mathematics) , artificial intelligence , pattern recognition (psychology) , image (mathematics) , focus (optics) , feature (linguistics) , satellite imagery , data mining , geography , land use , mathematics , engineering , linguistics , philosophy , civil engineering , optics , physics , pure mathematics , aerospace engineering
Satellite image classification has a vital role for the extraction and analysis of the useful satellite image information. This paper comprises the study of the satellite images classification and Remote Sensing along with a brief overview of the previous studies that are proposed in this field. In this paper, the existing work has been explained utilizing the classification techniques on satellite images of Alwar region in India that covers decent land cover features like Vegetation, Water, Urban, Barren, and Rocky regions. The post- implementation of the classification algorithms, the classified image is obtained displaying different classes that are represented by different colours. Each feature is represented by a different colour and can be easily perceived from the image obtained after classification. The focus of this study is on enhancing the classification accuracy by using proper classifiers along with the novel feature extraction techniques and pre-processing steps. Work of different authors is being discussed in a tabular form defining the methods and outcomes of the respective studies.