Recursive Estimation with Non-Homogeneous Image Models.

Abstract

This paper presents initial results on spatially variant recursive estimation of images. Parameters of block-wise constant recursive model are identified on noise free data. The models are then used to design reduced update Kalman filters which are applied to noisy data. The results are presented and discussed. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1978
Accession Number
ADA054115

Entities

People

  • Assad Radpour
  • Howard Kaufman
  • John Woods
  • Vinay K. Ingle

Organizations

  • Rensselaer Polytechnic Institute

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Coefficients
  • Computations
  • Decoding
  • Estimators
  • Filters
  • Filtration
  • Identification
  • Image Processing
  • Kalman Filtering
  • Kalman Filters
  • New York
  • Noise
  • Systems Engineering
  • Two Dimensional
  • White Noise

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.