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Activity Number:
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201
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, August 13, 2002 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Graphics*
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| Abstract - #301993 |
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Title:
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A Recursive Algorithm to Restore Images Based on Robust Estimation of NSHP Autoregressive Models
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Author(s):
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Ronny Vallejos*+ and Tomislav Mardesic
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Affiliation(s):
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University of Connecticut and University Tecnica Federico Santa Maria
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Address:
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215 Glenbrook Road, Storrs, CT, 06269-4120, USA
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Keywords:
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NSHP Autoregressive Model ; GM Estimator ; Additive Outlier ; Image Classification ; Restoration Algorithm
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Abstract:
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The objective of this paper is to present a new image restoration algorithm. This is a variation of the recursive algorithm introduced by Allende, Galbiati and Vallejos (2001). First, the image is classified in {k} categories. Then we assume that the gray levels in each category follow a NSHP autoregressive model. Robust estimation of the parameters of the model is considered to attenuate the effect of the image contamination on the parameters. In each iteration we will construct a new image using a robustified version of the residuals. The introduction of the classification techniques as a first step of the algorithm reduces considerably the number of parameters to estimate. So, the computational time is also reduced since the robust estimations of the parameters are solutions of nonlinear system of equations. Some applications are presented to real synthetic aperture radar (SAR) images to illustrate how our algorithm restores an image in practice.
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