A facet based road network detection procedure is described for radar imagery. The procedure includes a line detection part and a road detection and connection part. The line detection part analytically detects linear features using a facet Valley finding technique. Valleys are defined as zero crossings of the first directional derivatives of a bicubic facet model taken in a direction extremizing the second directional derivative. The road detection and connection part statistically screens the linear features on a component by component basis, and then optimally connects the screened linear features using a dynamic programming algorithm.
This thesis also includes as a preprocessing technique for noisy images, an adaptive noise removal algorithm, and suggests a practical method of estimating a local noise variance. / Master of Science
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/53080 |
| Date | January 1985 |
| Creators | Kim, Jungwhan John |
| Contributors | Computer Science and Applications |
| Publisher | Virginia Polytechnic Institute and State University |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | en_US |
| Detected Language | English |
| Type | Thesis, Text |
| Format | vii, 164 leaves, application/pdf, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
| Relation | OCLC# 13041554 |
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