Localized Ridgelet Transform-based detection of ship wakes in SAR images

This paper presents a Localized Ridgelet Transform(LRT) to detect ship wakes in Synthetic Aperture Radar (SAR) images. The key element of this technique is a localization of the ridgelet transform, whereby the intensity integration is performed in small windows rather than across the entire image. I...

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Bibliographic Details
Main Authors: Jianwei Li, Changwen Qu, Shujuan Peng
Format: Conference Proceeding
Language:English
Subjects:
Feature extraction
Kelvin
Linear feature
Localized Ridgelet transform
Marine vehicles
Radon
Ship wakes
Synthetic aperture radar
Wavelet transforms
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Summary:This paper presents a Localized Ridgelet Transform(LRT) to detect ship wakes in Synthetic Aperture Radar (SAR) images. The key element of this technique is a localization of the ridgelet transform, whereby the intensity integration is performed in small windows rather than across the entire image. In this algorithm, the transform space is subjected to processing which server to isolate and locate the response of linear features and suppress the responses of false alarms. This algorithm is tested on both synthetic images corrupted by various levels of noise and on actual SAR images of ship wakes. The results of this testing demonstrate the algorithm's robustness in the presence of noise, as well as its ability to detect and localize linear features that are significantly shorter than the image dimensions.
ISSN:2164-5221
DOI:10.1109/ICSP.2016.7877905