A Joint Detection-Estimation Approach to Boundary Estimation

Abstract

The estimation of object boundaries based on noisy observations is considered in the context of joint detection and estimation. The images are expressed as replacement processes and the boundaries modeled in terms of geometrical parameters associated with the object. The images studied have two textures, object and background, characterized by their first and second order statistics. A boundary processor consisting of optima estimator and detector is derived, for an appropriately chosen cost function. Differences between the cost function and resultant processor with other costs and estimator-detector pairs used previously in other applications is indicated. The optimal solution involves a nonlinear estimator and a detector with a variable threshold dependent on the estimator output.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1977
Accession Number
ADA044453

Entities

People

  • Simon Lopez-mora

Organizations

  • University of Southern California

Tags

Communities of Interest

  • C4I
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Change Detection
  • Data Science
  • Databases
  • Detection
  • Detectors
  • Estimators
  • Gaussian Noise
  • Image Processing
  • Information Processing
  • Information Science
  • Order Statistics
  • Random Variables
  • Statistical Algorithms
  • Statistical Inference
  • Statistics
  • Surveys

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Statistical inference.
  • Vision Science/Vision Psychology/Cognitive Neuroscience.