Iterative Methods for Estimation of 2-D AR Parameters Using a Data-Adaptive Toeplitz Approximation Algorithm

Abstract

A new two-dimensional data-adaptive algorithm utilizing the iterative Toeplitz approximation method is presented. This algorithm provides a robust and efficient means for accurate estimation of two-dimensional autoaggressive parameters representing spatially variant data arrays. Its convergence performance is comparable to that of the 2-D Recursive Least Squares (RLS) algorithm but is computationally more efficient. The savings in computation is realized by reducing the size of the matrix to be inverted when solving the AR model normal equation. The ability of the algorithm to be accurately estimate the model parameters using very small data sets and various windowing schemes are evaluated. Spectral estimates are compared for quarter-plane (QP), nonsymmetric half-plane (NSHP) and combined-quadrant (CQ) regions of support. Additionally, the algorithm is tested in noise cancellation and line enhancement applications using image arrays. This algorithm may be implemented for data- adaptive image processing or coding and for applications requiring 2-D spectral estimation.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1991
Accession Number
ADA246009

Entities

People

  • John C. Eremic

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Adaptive Filters
  • Algorithms
  • Cancellation
  • Classification
  • Computational Complexity
  • Data Sets
  • Electrical Engineering
  • Engineering
  • Equations
  • Image Processing
  • Image Restoration
  • Information Processing
  • Quadrants
  • Schools
  • Security
  • Signal Processing
  • Two Dimensional

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Approximation Theory.
  • Linear Algebra