Towards automatic recognition of wakes generated by dark vessels in sentinel-1 images

15Citations
Citations of this article
20Readers
Mendeley users who have this article in their library.

Abstract

The recognition of wakes generated by dark vessels is a tremendous and interesting challenge in the field of maritime surveillance by Synthetic Aperture Radar (SAR) images. The paper aims at assessing the detection performance in different scenarios by processing Sentinel-1 SAR images along with ground truth data. Results confirm that the Radon-based approach is an effective technique for wake-based detection of dark vessels, and they lead to a deeper understanding of the effects of different sea and wind conditions. In general, the best applicative scenario is a marine image characterized by homogeneous sea clutter; the presence of natural surface film or strong transition from low wind speed areas to more windy zones worsen the detection performance. Nonetheless, the proposed approach features dark vessel detection capabilities by identifying their wakes, without any a priori knowledge of their positions.

References Powered by Scopus

Deep learning for remote sensing data: A technical tutorial on the state of the art

1858Citations
N/AReaders
Get full text

Mask scoring R-CNN

940Citations
N/AReaders
Get full text

An automatic ship and ship wake detection system for spaceborne sar images in coastal regions

392Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Ship velocity estimation in SAR images using multitask deep learning

15Citations
N/AReaders
Get full text

Nonlinear Ship Wake Detection in SAR Images Based on Electromagnetic Scattering Model and YOLOv5

9Citations
N/AReaders
Get full text

Specific windows search for multi-ship and multi-scale wake detection in SAR images

8Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Graziano, M. D., & Renga, A. (2021). Towards automatic recognition of wakes generated by dark vessels in sentinel-1 images. Remote Sensing, 13(10). https://doi.org/10.3390/rs13101955

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 6

55%

Researcher 4

36%

Lecturer / Post doc 1

9%

Readers' Discipline

Tooltip

Engineering 7

70%

Decision Sciences 1

10%

Environmental Science 1

10%

Earth and Planetary Sciences 1

10%

Save time finding and organizing research with Mendeley

Sign up for free