satellite image classification in matlab
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Remote sensing is the method used to detect and measure target characteristics using electromagnetic energy in the form of heat, light and radio waves. Agriculture, disaster management, urban planning, water resources management, etc. The process of developing a thematic map from remote sensing images is called image classification. In one or more spectral bands digital numbers are used to represent spectral information. This information is used for the classification of digital images. Individual pixels are classified using this spectral information. Multispectral satellite images are used for classification. Image classification can be monitored and not monitored. The work deals with supervised classifiers namely minimum distance, support vector machine, maximum likelihood and parallelepiped. The performance of these classifiers is judged on the basis of kappa coefficient and overall accuracy.
The process of classifying satellite images involves grouping the pixel values of the image into meaningful categories. Several methods and techniques of classification of satellite images are available. The methods of classification of satellite images can be classified into three categories
1) automatic
2) manual and
3) hybrid.
All three methods have their own advantages and disadvantages. Most satellite image classification methods fall into the first category. The classification of satellite images requires the selection of the appropriate classification method based on the requirements. The present work of investigation is a study on methods and techniques of classification of images by satellite. The research also compares several comparative results of the researchers on satellite image classification methods.
Satellite imagery is rich and plays a vital role in providing geographic information. Satellite and remote sensing images provide quantitative and qualitative information that reduces the complexity of fieldwork and study time. Satellite remote sensing technologies collect data / images at regular intervals. The volumes of data received in data centers is huge and is growing exponentially as technology is growing at rapid speed as timely and volumes of data have been growing at an exponential rate. There is a strong need for effective and efficient mechanisms to extract and interpret valuable information from massive satellite imagery. Satellite imagery is a powerful technique for extracting information from a large number of satellite images.
It can be understood in the following video: