Keywords : Principle Component Analysis


Best Band Selection using Principle Component Analysis Algorithm from Remote Sensing Data

Maha A. Hasso; Mona J. Siddiq

AL-Rafidain Journal of Computer Sciences and Mathematics, 2010, Volume 7, Issue 3, Pages 135-144
DOI: 10.33899/csmj.2010.163933

The best band selection from remote sensing image plays an important roles in multispectral and hyperspectral remote sensing image processing due  to the intercorrelation that inherent in the multispectral images taken by remote sensing sensors.
In this paper we use principle component analysis  algorithm applied on remote sensing data and find covariance matrix for bands that should be processed then find eigen vector using Jacobi methods .The algorithm was  applied on multispectral images of Thematic Mapper sensor , it concluded that the six  band was  the best band , the value of it’s eigen value    was the biggest one  and the value of signal to noise ratio equals to 74.7217. This algorithm is constructed using  Visual C# 2008 that is characterized by efficient and high speed implementation.