An Effective Shadow Extraction Method for SAR Images
Article No.: 56, Pages 1 - 8
Abstract
Since the target's shadow in a synthetic aperture radar (SAR) image can provide significant features, it is becoming a crucial discriminative feature for interpreting SAR images. In this paper, we propose a new segmentation method based on simple linear iterative clustering (SLIC) superpixel segmentation and merging to extract the targets' shadow regions in SAR images. The process is divided into four stages. Firstly, the original SAR image is preprocessed using logarithmic transform and anisotropic diffusion filtering. Secondly, the preprocessed image is segmented with the SLIC method. Then, we propose a technique based on the shadow superpixel marker to merge superpixels to obtain the shadow region. Finally, the merged edge of the shadow region is smoothed using the morphological closing operation to get the final shadow detection result. The experimental results based on the public Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset demonstrate the feasibility of the proposed method.
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- An Effective Shadow Extraction Method for SAR Images
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Published In
May 2023
711 pages
ISBN:9798400708237
DOI:10.1145/3604078
Copyright © 2023 ACM.
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Association for Computing Machinery
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Published: 26 October 2023
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ICDIP 2023
ICDIP 2023: The 15th International Conference on Digital Image Processing
May 19 - 22, 2023
Nanjing, China
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