1. ERDC Knowledge Core
  2. Engineer Research and Development Center (ERDC)
  3. Geospatial Research Laboratory (GRL) (formerly Topographic Engineering Center (TEC))
  4. Publication
  5. Research Note
Please use this identifier to cite or link to this item: https://hdl.handle.net/11681/5067
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dc.contributor.authorRand, Robert S.-
dc.contributor.authorShine, James A.-
dc.date.accessioned2016-03-18T14:35:33Z-
dc.date.available2016-03-18T14:35:33Z-
dc.date.issued1983-10-
dc.identifier.urihttp://hdl.handle.net/11681/5067-
dc.descriptionResearch note-
dc.descriptionAbstract: The Laws Texture Measure was tested in an autoevaluation experiment and compared to some of the texture measures previously studied at ETL. In addition, four methods of component reduction were evaluated. Laws Texture was found to be the most effective measure for identifying a Buildings/Roads class; however, it was less effective on other classes. A technique that transforms the original components into principal components and then arranges the transformed components in an order that maximizes the divergence was selected as the most effective component reduction method.-
dc.publisherU.S. Army Engineer Topographic Laboratories.-
dc.publisherEngineer Research and Development Center (U.S.)-
dc.relationhttp://acwc.sdp.sirsi.net/client/en_US/search/asset/1047514-
dc.relation.ispartofseriesETL ; 0343.-
dc.rightsApproved for public release; distribution is unlimited.-
dc.sourceThis Digital Resource was created from scans of the Print Resource.-
dc.subjectBayes Classifier-
dc.subjectDigital imagery-
dc.subjectDivergence-
dc.subjectLaws texture measure-
dc.subjectPattern recognition-
dc.subjectPrincipal components-
dc.titleFeature analysis and reduction of laws texture measure-
dc.typeReporten_US
Appears in Collections:Research Note

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