Applications of Texture Analysis for Rock Types Discrimination

Abstract

Aimed at developing image processing methods for rock types analysis with LANDSAT data, numerous experiments were conducted using supervised and unsupervised classification techniques under the general concept of texture analysis with LANDSAT digital data covering two geological quads of Nevada. The results indicate that the supervised classification method is very effective in the extraction of ranite regions when (1) data were in ratio format, (2) feature variables included both tone and texture information, and (3) the classifier is capable of handling non-normally distributed data. Classification errors occurred when there exists pixels of non-granite category whose spectral and textural properties are statistically similar to that of granite pixels. Two cases of errors can be noted: Type 1 pixels located at the periphery of the granite regions, and Type 2 pixels located far away from the core of the granite areas.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1983
Accession Number
ADA142268

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  • S. Hsu

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  • Engineered Resilient Systems

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Artificial Intelligence
  • Boundaries
  • Composite Materials
  • Computer Vision
  • Data Analysis
  • Digital Information
  • Geography
  • Image Processing
  • Information Science
  • Jet Propulsion
  • Machine Learning
  • Pattern Recognition
  • Recognition
  • Supervised Machine Learning
  • Unsupervised Machine Learning

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  • Computer science

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  • Computer Vision.
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