• Phulen Mahato

In this work, a methodology been proposed for classification of a user fed HSI image into a predefined group. To achieve our target at first a data base of image group is constructed. The methodology begins with feeding an unknown image by user. This raw image consists of many noises, hence a data preprocessing is carried out for noise removal, followed by a procedure for band reduction. Here we have incorporated a methodology for reduction of the number of bands from 200 to 50, resulting in an improvement in execution time. Finally incorporating the concept of a vector machine, the target classification has obtained. The proposed method is quiet successful for image classification in comparison of some popular image classification methods.

HSI image classification, noise removal, data preprocessing, band reduction, vector machine.

"Vector Classifier - An Amalgamated method for Hyper Spectral Image classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 9, page no.f732-f736, September-2023, Available :http://www.jetir.org/papers/JETIR2309588.pdf

"Vector Classifier - An Amalgamated method for Hyper Spectral Image classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 9, page no. ppf732-f736, September-2023, Available at : http://www.jetir.org/papers/JETIR2309588.pdf