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Proceedings Paper

Visualization using rational morphology and magnitude reduction II
Author(s): Robert G. Kogan; Sos S. Agaian; Karen Panetta Lentz
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Paper Abstract

Morphological filters are investigated and employed for detecting and visualizing objects within an image. The techniques developed here will be employed on NASA's Earth Observing System (EOS) satellite data products for the purpose of anomaly detection. Previous efforts have shown the phase information in the spectral domain to be more significant than the magnitude information in representing the location of objects in an image. The magnitude information does provide some useful information for object location, but it is also sensitive to image illumination, blurring, and magnification variations, all of which influence the performance of object detection algorithms. Magnitude reduction techniques in the spectral domain can dramatically improve subsequent object detection methods by causing them to rely less on the magnitude and more on the phase information of the image. We propose three new improvements to our object enhancement and detection techniques. Our first method is an enhancement to our previous magnitude-reduction technique. Our second improvement is a modification of our Rational Morphological Filters in which we raise our resulting image to a power, thereby magnifying our feature detection capability. Third, we look at speed enhancement by utilizing Hartley and Walsh Transforms in place of classical Fourier techniques.

Paper Details

Date Published: 6 July 1998
PDF: 12 pages
Proc. SPIE 3387, Visual Information Processing VII, (6 July 1998); doi: 10.1117/12.316419
Show Author Affiliations
Robert G. Kogan, Tufts Univ. (United States)
Sos S. Agaian, Univ. of Texas at San Antonio (United States)
Karen Panetta Lentz, Tufts Univ. (United States)

Published in SPIE Proceedings Vol. 3387:
Visual Information Processing VII
Stephen K. Park; Richard D. Juday, Editor(s)

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