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dc.contributor.authorBostater, Charles R.
dc.date.accessioned2017-06-06T16:21:19Z
dc.date.available2017-06-06T16:21:19Z
dc.date.issued2006-10-11
dc.identifier.citationBostater Jr., C. R. (2006). Optimal band selection for hyperspectral remote sensing of aquatic benthic features - a wavelet filter window approach. Paper presented at the Proceedings of SPIE - the International Society for Optical Engineering, 6360 doi:10.1117/12.687494en_US
dc.identifier.urihttp://hdl.handle.net/11141/1472
dc.description.abstractThis paper describes a wavelet based approach to derivative spectroscopy. The approach is utilized to select, through optimization, optimal channels or bands to use as derivative based remote sensing algorithms. The approach is applied to airborne and modeled or synthetic reflectance signatures of environmental media and features or objects within such media, such as benthic submerged vegetation canopies. The technique can also applied to selected pixels identified within a hyperspectral image cube obtained from an board an airborne, ground based, or subsurface mobile imaging system. This wavelet based image processing technique is an extremely fast numerical method to conduct higher order derivative spectroscopy which includes nonlinear filter windows. Essentially, the wavelet filter scans a measured or synthetic signature in an automated sequential manner in order to develop a library of filtered spectra. The library is utilized in real time to select the optimal channels for direct algorithm application. The unique wavelet based derivative filtering technique makes us of a translating, and dilating derivative spectroscopy signal processing (TDDSSP®) approach based upon remote sensing science and radiative transfer processes unlike other signal processing techniques applied to hyperspectral signatures.en_US
dc.language.isoen_USen_US
dc.rightsThis published article is made available in accordance with publishers policy. It may be subject to U.S. copyright law.en_US
dc.rights.urihttp://spie.org/publications/journals/guidelines-for-authors#Terms_of_Useen_US
dc.titleOptimal band selection for hyperspectral remote sensing of aquatic benthic features - a wavelet filter window approachen_US
dc.typeConference Proceedingen_US
dc.identifier.doi10.1117/12.687494


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