Segmenting Shadows from synthetic aperture radar imagery using edge-enhanced region growing

Gregory J. Power; Kelce S. Wilson

doi:10.1117/12.405840

2 November 2000 Segmenting Shadows from synthetic aperture radar imagery using edge-enhanced region growing

Gregory J. Power, Kelce S. Wilson

Proceedings Volume 4113, Algorithms and Systems for Optical Information Processing IV; (2000) https://doi.org/10.1117/12.405840
Event: International Symposium on Optical Science and Technology, 2000, San Diego, CA, United States

Abstract

An enhanced region-growing approach for segmenting regions is introduced. A region-growing algorithm is merged with stopping criteria based on a robust noise-tolerant edge-detection routine. The region-grow algorithm is then used to segment the shadow region in a Synthetic Aperture Radar (SAR) image. This approach recognizes that SAR phenomenology causes speckle in imagery even to the shadow area due to energy injected from the surrounding clutter and target. The speckled image makes determination of edges a difficult task even for the human observer. This paper outlines the edge-enhanced region grow approach and compares the results to three other segmentation approaches including the region-grow only approach, an automated-threshold approach based on a priori knowledge of the SAR target information, and the manual segmentation approach. The comparison is shown using a tri-metric inter- algorithmic approach. The metrics used to evaluate the segmentation include percent-pixels same (PPS), the partial- directed hausdorff (PDH) metric, and a shape-based metric based on the complex inner product (CIP). Experimental results indicate that the enhanced region-growing technique is a reasonable segmentation for the SAR target image chips obtained from the Moving and Stationary Target Acquisition and Recognition (MSTAR) program.

Citation Download Citation

Gregory J. Power and Kelce S. Wilson "Segmenting Shadows from synthetic aperture radar imagery using edge-enhanced region growing", Proc. SPIE 4113, Algorithms and Systems for Optical Information Processing IV, (2 November 2000); https://doi.org/10.1117/12.405840

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