• Sorted by Date • Classified by Publication Type • Sorted by First Author Last Name • Classified by Author Last Name •
D. W. Starr and Alan K. Mackworth. Exploiting Spectral, Spatial and Semantic Constraints in the Segmentation of Landsat Images. Canadian Journal of Remote Sensing, 4(2):102–107, 1979.
A critique of traditional classification techniques for LANDSAT images and consideration of some scene analysis techniques, exploiting spatial organization and meaning, lead to a new approach to computer programs for LANDSAT image understanding. To justify this approach, a program that combines modified maximum likelihood techniques with interpretation-controlled region merging methods to interpret forest cover in LANDSAT images is described. For comparison purposes, a pure supervised classifier using the same data made 43% more errors and produced a segmentation twice as complex.
@Article{StarrCJRS79,
author = {D. W. Starr and Alan K. Mackworth},
title = {Exploiting Spectral, Spatial and Semantic Constraints in the Segmentation of Landsat Images},
year = {1979},
journal = {Canadian Journal of Remote Sensing},
volume = {4},
number = {2},
pages = {102--107},
abstract = {A critique of traditional classification techniques for LANDSAT images and consideration of some scene analysis techniques, exploiting spatial organization and meaning, lead to a new approach to computer programs for LANDSAT image understanding. To justify this approach, a program that combines modified maximum likelihood techniques with interpretation-controlled region merging methods to interpret forest cover in LANDSAT images is described. For comparison purposes, a pure supervised classifier using the same data made 43% more errors and produced a segmentation twice as complex.},
bib2html_pubtype ={Refereed Journal},
bib2html_rescat ={},
}
Generated by bib2html.pl (written by Patrick Riley ) on Wed Apr 23, 2014 19:08:34