CSEIT1722312 | Received : 16 April 2017 | Accepted : 24 April 2017 | March-April-2017 [(2)2: 1000-1004] International Journal of Scientific Research in Computer Science, Engineering and Information Technology © 2017 IJSRCSEIT | Volume 2 | Issue 2 | ISSN : 2456-3307 1000 Comparative Study of Algorithms for Hyper Spectral Image Classification Pallavi Juyal, Manish Jain, Varsha Nemade Department Computer Engineering, Mukesh Patel School of Technology Management and Engineering, Mumbai, Maharashtra, India ABSTRACT Now days the use of remote sensing imagery has increased drastically, ranging from the applications in farms to that in the field of defense. These images range from hyper spectral, multispectral to ultra spectral. One of the major applications of the remote sensing image is that of classification of the image. Several algorithms have been found for classification of images based on various factors. The algorithms used for classification are either supervised or unsupervised. In this paper we study different algorithms used for classification of the hyper spectral images. An analysis of the output obtained by the implementation of various algorithms has also been done. The analysis has been done based on the number of pixels classified. Keywords : Remote sensing, hyperspectral image, classification, classifier, spectrum, electromagnetic spectrum, Euclidian distance. I. INTRODUCTION Remote sensing refers to the collection and analysis of data that is acquired by a satellite type instrument.With an example, remote sensing can be explained as follows, if we take the picture of a school building and in the picture we see that it is composed of doors, windows and roof all of which appear to be of different colour, this is remote sensing. Remote sensing deals with these three components, a platform is needed to hold the instrument,a target object to be acquired and then observed and an instrument or a detector to sense and observe the target. The image shown below is an explanation of how remote sensing is actually performed. Figure 1. Acquisition of Satellite Image A hyper spectral imaging like any other multispec image deals essentially with the collection and processing of information by making use of the electromagnetic spectrum which is the range of all types of EM radiation. The naked human eye colour sees only colour in 3 bands, the RGB whereas a spectrum image separate the image into multiple bands. This technique of dividing the image into various different spectrums is far beyond the visible. Below is shown a hyper spectral image which will be used as a input in the implementation of the classification algorithm. Figure 2. The Image to be used as input