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 | |