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Optical Engineering

Evaluation Of Image Restoration Filters For Machine Classification
Author(s): D. C. Lai; J. Potenza; K. Verfaille
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Paper Abstract

Image restoration filters are known to improve the subjective quality of a picture. However, it is not evident that the filters would facilitate further machine processing such as machine classification. In this paper, several image restoration filters are evaluated and compared based on their perfor-mances in machine classification under various blur and noise conditions to assess their usefulness for automatic classification. An experiment has been specifically designed and conducted for this purpose. Appropriate performance measures are derived. The results show that, under certain combinations of blur and noise conditions, the filters do improve machine classification.

Paper Details

Date Published: 1 December 1984
PDF: 7 pages
Opt. Eng. 23(6) doi: 10.1117/12.7973385
Published in: Optical Engineering Volume 23, Issue 6
Show Author Affiliations
D. C. Lai, The University of Vermont (United States)
J. Potenza, The University of Vermont (United States)
K. Verfaille, The University of Vermont (United States)

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