Exploration of Unmixing and Classification of Hyperspectral Imagery

Hyperspectral imaging is the vital method and an effective tool to quantify as well identify dissimilar objects from remotely recognsized spectral information. Using OMEGA instrument, the Mars region is imaged using an unprecedented spatial and spectral combination of resolution spectrometer. Hyperspectral images provide high resolution, and its spectral range gives the ability to identify chemical mixture in the atmosphere of Mars more precisely than before. Due to the inadequate spatial resolution of Hyperspectral sensors mixed pixel arises. Such mixed pixels contain more than one distinct material, which is called endmembers. These hyperspectral images provide good resolution, and the range of spectra will give the ability to identify the chemical species present in the atmosphere of Mars more accurately than before. The proposed methodology is evaluated on the real hyperspectral datasets. The integration of unmixing algorithm termed "Non-Linear Hybrid Approach for Regularized Simultaneous Forward-Backward Greedy Algorithm (NonLHA-RSFBGA)" with the Singular Spectrum Analysis approach, resulting in a better level of classification using the ART classifier for the identification/classification of the Mineral endmember.