Computational efficient unsupervised coastline detection from single-polarization 1-look SAR images of complex coastal environments

Andrea Garzelli; Claudia Zoppetti; Gianpaolo Pinelli

doi:10.1117/12.2278688

4 October 2017 Computational efficient unsupervised coastline detection from single-polarization 1-look SAR images of complex coastal environments

Andrea Garzelli, Claudia Zoppetti, Gianpaolo Pinelli

Author Affiliations +

Proceedings Volume 10427, Image and Signal Processing for Remote Sensing XXIII; 1042714 (2017) https://doi.org/10.1117/12.2278688
Event: SPIE Remote Sensing, 2017, Warsaw, Poland

Abstract

Coastline detection in synthetic aperture radar (SAR) images is crucial in many application fields, from coastal erosion monitoring to navigation, from damage assessment to security planning for port facilities. The backscattering difference between land and sea is not always documented in SAR imagery, due to the severe speckle noise, especially in 1-look data with high spatial resolution, high sea state, or complex coastal environments. This paper presents an unsupervised, computationally efficient solution to extract the coastline acquired by only one single-polarization 1-look SAR image. Extensive tests on Spotlight COSMO-SkyMed images of complex coastal environments and objective assessment demonstrate the validity of the proposed procedure which is compared to state-of-the-art methods through visual results and with an objective evaluation of the distance between the detected and the true coastline provided by regional authorities.

Conference Presentation

Citation Download Citation

Andrea Garzelli, Claudia Zoppetti, and Gianpaolo Pinelli "Computational efficient unsupervised coastline detection from single-polarization 1-look SAR images of complex coastal environments ", Proc. SPIE 10427, Image and Signal Processing for Remote Sensing XXIII, 1042714 (4 October 2017); https://doi.org/10.1117/12.2278688

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