FAST MULTICHANNEL APPROACH TO ADAPTIVE ESTIMATION AND FILTERING OF TWO DIMENSIONAL IMAGES.

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Title

FAST MULTICHANNEL APPROACH TO ADAPTIVE ESTIMATION AND FILTERING OF TWO DIMENSIONAL IMAGES. (EN)

Creator

Boutalis, Yiannis (EN)

Carayannis, George (EN)

Kollias, Stefanos (EN)

Type

conferenceItem (EN)

Conference item (EN)

Issued

2014-03-01T02:40:50Z

1987 (EN)

Year

1987 (EN)

Description

A fast, computationally efficient method for adaptive image estimation is presented. The method is based on the multichannel form of the fast a posteriori error sequential technique (FAEST) for the estimation of the parameters of two-dimensional autoregressive (AR) models. These models are designed to have the shift invariance property necessary for fast recursive least squares techniques. Inclusion of a forgetting factor, or of a sliding window in the algorithm, permits adaptive image model parameter estimation. The specific properties of the algorithm are examined and it is shown that the proposed estimation scheme is much faster than other existing approaches. Various interesting applications of the method are dicussed and examples are given which illustrate the theoretical results. (EN)

Subject

Parameter Estimation (EN)

MATHEMATICAL TECHNIQUES - Least Squares Approximations (EN)

IMAGE PROCESSING (EN)

Ar Model (EN)

Adaptive Estimation (EN)

Image Modeling (EN)

Shift Invariant (EN)

Sliding Window (EN)

AUTOREGRESSIVE MODELS (EN)

SIGNAL FILTERING AND PREDICTION (EN)

Fast Recursive Least Squares (EN)