A Research Review on Hyperspectral Data Processing and Analysis Algorithms

Abstract Recent advances in the sensors technology for imaging spectroscopy coupled with high computing power, raise the demand to develop the algorithms for processing and analysis of hyperspectral data for various applications. Well known techniques and algorithms are available for processing multispectral data in the literature. Researchers tried to use similar approaches for hyperspectral data analysis and succeeded up to some extent. Several techniques for atmospheric correction, dimensionality reduction, endmember extraction and classification has been developed and reported accordingly. To process and evaluate the hyperspectral data for domain applications require generalized framework. This article critically reviews most of the existing hyperspectral data processing and analysis approaches and gives generalized framework. Which offers considerate view for future potential and focuses emerging challenges in the development of robust algorithms for hyperspectral data processing and analysis.

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