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COMPUTER CLASSIFICATION OF REMOTELY SENSED MULTISPECTRAL IMAGE DATA BY EXTRACTION AND CLASSIFICATION OF HOMOGENEOUS OBJECTS

机译:通过均匀物体的提取和分类对遥感多光谱图像数据进行计算机分类

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摘要

A method of classification of digitized multispectral images is developed and experimentally evaluated on actual earth resources data collected by aircraft and satellite. The method is designed to exploit the characteristic dependence between adjacent states of nature that is neglected by the more conventional simple-symmetric decision rule. Thus contextual information is incorporated into the classification scheme. The principle reason for doing this is to improve the accuracy of the classification. For general types of dependence this would generally require more computation per resolution element than the simple-symmetric classifier. But when the dependence occurs in the form of "redundance", the elements can be classified collectively, in groups, thereby reducing the number of classifications required. Thus a potential exists for increased, rather than decreased, efficiency.

著录项

  • 作者

    ROBERT L. KETTIG;

  • 作者单位
  • 年度 1975
  • 页码 1-194
  • 总页数 194
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 工业技术;
  • 关键词

  • 入库时间 2022-08-29 11:11:06

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