Algorithm for Segmentation of Multichannel Images.

Abstract

Segmentation is an important step in the computer based analysis of images. This thesis addresses the segmentation of images of multiple channels of data. Such images are referred to as multichannel images. Examples of these are color images, where the channels represent color components, and remote sensing data, where the channels may represent signals from various visible and infrared frequency bands. This thesis describes and demonstrates how segmentation of multichannel images into homogeneous regions can be accomplished using linear predictive filtering. Results are given for some synthetically generated color images of two textures. Keywords include: Multichannel images, Segmentation, Maximum Likelihood, and Maximum A Posteriori.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1985
Accession Number
ADA166215

Entities

People

  • James F. Janecek

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Human Systems
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Classification
  • Computer Programs
  • Computer Vision
  • Computers
  • Electrical Engineering
  • Engineering
  • Filtration
  • Frequency
  • Image Processing
  • Image Segmentation
  • Operating Systems
  • Probability
  • Schools
  • Two Dimensional
  • United States

Fields of Study

  • Engineering

Readers

  • Atmospheric Remote Sensing.
  • Neural Network Machine Learning.
  • Radio communications and signal processing.