Accession Number:

AD0759505

Title:

Texture Tone Study. Classification Experiments.

Descriptive Note:

Interim technical rept. no. 4,

Corporate Author:

KANSAS UNIV/CENTER FOR RESEARCH INC LAWRENCE REMOTE SENSING LAB

Report Date:

1972-12-31

Pagination or Media Count:

207.0

Abstract:

Four aerial photographic image data sets were classified on the basis of a large class of quickly computable textural features. When the most appropriate features and decision rule were selected, identification accuracy on the order of 75 per cent was obtained for 9 to 11 terrain categories. Conclusions drawn from these experiments suggest That the most powerful features are the entropy and inverse difference features measured at distance 1 and at distance 110th the length of the image side That the class of quickly computable textural features needs to be supplemented by tonal and context features in order for better identification to be obtained. This second conclusion is not to be unexpected since a photointerpreter who tries to make interpretations on the basis of a 18 inch x 18 inch squared specially processed for high contrast on a 9 inch x 9 inch 120,000 aerial photograph does not do any better than 75 per cent correct identification as previously reported. Author

Subject Categories:

  • Cartography and Aerial Photography
  • Computer Programming and Software
  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE