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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Proceedings of the National Academy of Sciences, India Section A: Physical Sciences
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
