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Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information

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Accurate Ship Detection Using Electro-Optical Image-Based Satellite on Enhanced Feature and Land Awareness.

Sang-Heon Lee^1,2, Hae-Gwang Park³, Ki-Hoon Kwon¹

¹School of Electronics Engineering, Kyungpook National University, Daegu 41566, Republic of Korea.

Sensors (Basel, Switzerland)

|December 11, 2022

Summary

This study introduces a novel algorithm to enhance ship detection in satellite imagery, significantly improving accuracy by addressing challenges like clouds and land-based false positives. The method boosts detection performance for various ship types.

Keywords:

convolution neural network image enhancement satellite photography ship detection

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Area of Science:

Remote Sensing
Computer Vision
Artificial Intelligence

Background:

Ship detection in high-resolution electro-optical satellite images faces challenges from environmental factors like clouds, waves, and shadows.
False detections frequently occur in land areas due to image similarities with ships.

Purpose of the Study:

To develop and evaluate an algorithm that enhances ship detection accuracy in satellite imagery.
To overcome limitations of existing methods in handling environmental interferences and land-based false alarms.

Main Methods:

Proposed a three-stage algorithm: Global Feature Enhancement Pre-processing (GFEP) for contrast improvement, Multiclass Ship Detector (MSD) for candidate extraction, and False Detected Ship Exclusion by Sea Land Segmentation Image (FDSESI) for land-based false positive removal.
Utilized high-resolution electro-optical satellite images, including five ship classes, across a database of 1984 images.

Main Results:

The proposed method achieved a mean average precision (mAP) of 63.39%, a notable improvement from baseline deep learning algorithms.
Demonstrated significant enhancement in ship detection accuracy compared to existing methods.

Conclusions:

The integrated GFEP, MSD, and FDSESI algorithm effectively improves ship detection accuracy in challenging satellite imagery.
The developed approach offers a robust solution for reliable ship detection, crucial for maritime surveillance and monitoring.