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Remote sensing HSI classification and estimation of MIMETITE mineral spectral signatures from ISRO, India

The availability of facilities for interpreting and analyzing satellite data is an important element for the extensive utilization of remote sensing data. Remote sensing is the area where HSI is considered for the various applications. The high dimensional hyperspectral images contains a lot of redundant Information and the signal information is usually concentrated on lower dimensional subspaces. The dimension reduction based on complex wavelet filter bank approach is carried out on the mimetite mineral spectral signatures and classified using the orthogonal subspace projection method. The correlation of first twenty spectral signatures of mimetite mineral sample taken from ISRO, RRSSC, Nagpur is found out and with the threshold, the redundant information is ignored. With this combination of dimension reduction and classification, the results would be quite better. The undesired spectral signatures are efficiently rectified with the help of OSP. The desired mimetite spectral signature is segregated from the mixed pixel and estimated in the presence of other two minerals viz scorodite and colomanite with the help of complex wavelet filter bank and spectral matching.