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Proceedings Paper

Efficient edge detection by scale adaptation and recursive half-space filtering
Author(s): Melba M. Crawford; Pui Fun Lau
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Paper Abstract

A new edge detection algorithm has been developed and implemented that has both good speed and accuracy properties. The accuracy of the approach is derived from scale adaptation through anisotropic diffusion. The speed of the filter is based on recursive filtering. Specifically, the algorithm is implemented through a decomposition of the recursive filter into a convolution of two independent half space filters. This further improves the speed of the recursive filter and facilitates scale adaptation. The resulting algorithm is 1 - 2 orders of magnitude faster than comparable Gaussian based frequency domain and spatial domain methods. The new filter is omni-directional and super-elongated. It is also contour following, has computational complexity which is independent of scale, and has no truncation noise. The algorithm has been implemented and successfully applied to SPOT XS and Landsat MSS and TM imagery as one component of a region based image segmentation scheme.

Paper Details

Date Published: 15 November 1993
PDF: 11 pages
Proc. SPIE 1938, Recent Advances in Sensors, Radiometric Calibration, and Processing of Remotely Sensed Data, (15 November 1993); doi: 10.1117/12.161567
Show Author Affiliations
Melba M. Crawford, Univ. of Texas/Austin (United States)
Pui Fun Lau, IBM Corp. (United States)


Published in SPIE Proceedings Vol. 1938:
Recent Advances in Sensors, Radiometric Calibration, and Processing of Remotely Sensed Data
Pat S. Chavez; Robert A. Schowengerdt, Editor(s)

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