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Illumination and shadow compensation of hyperspectral images using a digital surface model and non-linear least squares estimation
Swedish Defence Research Agency, Linköping, Sweden.
Swedish Defence Research Agency, Linköping, Sweden.
Termisk Systemteknik, Linköping, Sweden.ORCID iD: 0000-0002-6763-5487
2011 (English)In: Proc. SPIE 8180, Image and Signal Processing for Remote Sensing XVII / [ed] Lorenzo Bruzzone, SPIE - International Society for Optical Engineering, 2011, Art.nr 8180-26- p.Conference paper (Refereed)
Abstract [en]

Object detection and material classification are two central tasks in electro-optical remote sensing and hyperspectral imaging applications. These are challenging problems as the measured spectra in hyperspectral images from satellite or airborne platforms vary significantly depending on the light conditions at the imaged surface, e.g., shadow versus non-shadow. In this work, a Digital Surface Model (DSM) is used to estimate different components of the incident light. These light components are subsequently used to predict what a measured spectrum would look like under different light conditions. The derived method is evaluated using an urban hyperspectral data set with 24 bands in the wavelength range 381.9 nm to 1040.4 nm and a DSM created from LIDAR 3D data acquired simultaneously with the hyperspectral data

Place, publisher, year, edition, pages
SPIE - International Society for Optical Engineering, 2011. Art.nr 8180-26- p.
Series
, Proceedings of SPIE, ISSN 0277-786X ; 8180
Keyword [en]
hyperspectral, shadows, illumination model, digital surface model
National Category
Remote Sensing
Identifiers
URN: urn:nbn:se:liu:diva-120507DOI: 10.1117/12.898084ISBN: 9780819488077OAI: oai:DiVA.org:liu-120507DiVA: diva2:845461
Conference
Image and Signal Processing for Remote Sensing XVII, Prague, Czech Republic, 19–21 September 2011
Available from: 2015-08-12 Created: 2015-08-12 Last updated: 2015-09-22Bibliographically approved

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Friman, OlaAhlberg, Jörgen
Remote Sensing

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