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Proceedings Paper

Resolvable analysis and synthesis of synthetic aperture radar imagery
Author(s): Wolfgang F. Kraske
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Paper Abstract

The segmentation and representation of complex features in imagery is of great importance for automatic target recognition and human perception of image features. Multiresolution image representation paradigms are currently being pursued to provide a hierarchical framework for efficient analysis and compression of image data for machine recognition and human perception of image features. Grayscale mathematical morphology is playing an emerging role as a multiscale image representation operator. IN particular, grayscale morphology utilizes set operations, requiring only computer addition and comparison, with tractable shapes of varying size and orientation. For practical implementation, the nonlinear filters of mathematical morphology may be cascaded without precision loss by exploiting the finite characteristic of digital computers and avoiding the constricting and abstract Fourier space requirements of linear filtering techniques, such as wavelet theory. This paper presents morphological filter operations which use oriented line shapes or structuring elements in comparison with image data to extract and analyze line and textural features within a hierarchical framework and representation paradigm. A median line filter is defined by the maximum of oriented 1-D erosions, median erosion, or the minimum of oriented 1-D dilations, median dilation. A cascade of these operations to form an image pyramid or a morphological skeleton are investigated as plausible representation paradigms. Smoothing and differencing operations are exploited to provide multiscale complimentary feature representations similar to the wavelet base.

Paper Details

Date Published: 1 November 1992
PDF: 10 pages
Proc. SPIE 1826, Intelligent Robots and Computer Vision XI: Biological, Neural Net, and 3D Methods, (1 November 1992); doi: 10.1117/12.131610
Show Author Affiliations
Wolfgang F. Kraske, Northrop Corp. (United States)


Published in SPIE Proceedings Vol. 1826:
Intelligent Robots and Computer Vision XI: Biological, Neural Net, and 3D Methods
David P. Casasent, Editor(s)

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