Incorporation of texture in multispectral synthetic image generation tools

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dc.contributor.author Schott, John en_US
dc.contributor.author Salvaggio, Carl en_US
dc.contributor.author Brown, Scott en_US
dc.contributor.author Rose, Robert en_US
dc.date.accessioned 2007-07-05T14:07:58Z en_US
dc.date.available 2007-07-05T14:07:58Z en_US
dc.date.issued 1995-06 en_US
dc.identifier.citation Targets and Backgrounds: Characterization and Representation 2469 (1995) 189-196 en_US
dc.identifier.issn 0277-786X en_US
dc.identifier.uri http://hdl.handle.net/1850/4230 en_US
dc.description RIT community members may access full-text via RIT Libraries licensed databases: http://library.rit.edu/databases/
dc.description.abstract The Digital Imaging and Remote Sensing Synthetic Image Generation (DIRSIG) model emphasizes quantitative prediction of the radiance reaching sensors with bandpass values between 0.28 and 20.0 jim. The model embodies a rigorous end-to-end speciral modeling of radiation propagation, absorption and scattering, target temperatures based on meteorological history, extensive directional target-background interactions and detector responsivities.1 This paper describes texture quantification, the spectral-spatial correlation of textures, texture collection and generation methods. Finally, we will describe how DIRSIG generates texture on a pixel by pixel basis and maintains the spectral correlation of targets between bands. en_US
dc.description.sponsorship n/a en_US
dc.language.iso en_US en_US
dc.publisher The International Society for Optical Engineering (SPIE) en_US
dc.relation.ispartofseries vol. 2469 en_US
dc.title Incorporation of texture in multispectral synthetic image generation tools en_US
dc.type Article en_US
dc.subject.keyword Remote sensing en_US
dc.subject.keyword Synthetic image generation en_US
dc.subject.keyword Texture en_US
dc.identifier.url http://dx.doi.org/10.1117/12.210590

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