SAR Ship Detection Using Image Histograms and Machine Learning Approach

Detection of objects through remote sensing is a current research area. Ship detection in SAR images is a very intense research area today. Convenience is provided to those concerned in applications such as military surveillance and tracking of commercial ships. In this study, ship images were classified using the Hessian matrix and HOG algorithm. Using the eigenvalues of the Hessian matrix, the angle and orientation information of the HOG method was calculated. Thus, distinctive pixel characteristics were coded. The proposed method has achieved successful results in experimental studies.

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Publication Details

Journal
Türk doğa ve fen dergisi :/Türk doğa ve fen dergisi
Published
2024-09-26
DOI
https://doi.org/10.46810/tdfd.1528267
Primary Topic
Remote-Sensing Image Classification
Type
article
Field-Weighted Citation Impact
0.00

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article

SAR Ship Detection Using Image Histograms and Machine Learning Approach

Mücahit Çalışan, Kazım Hanbay, Taha Burak Özdemіr
Türk doğa ve fen dergisi :/Türk doğa ve fen dergisi
Remote-Sensing Image Classification
article

SAR Ship Detection Using Image Histograms and Machine Learning Approach

Mücahit Çalışan, Kazım Hanbay, Taha Burak Özdemіr
article en

Abstract

Detection of objects through remote sensing is a current research area. Ship detection in SAR images is a very intense research area today. Convenience is provided to those concerned in applications such as military surveillance and tracking of commercial ships. In this study, ship images were classified using the Hessian matrix and HOG algorithm. Using the eigenvalues of the Hessian matrix, the angle and orientation information of the HOG method was calculated. Thus, distinctive pixel characteristics were coded. The proposed method has achieved successful results in experimental studies.

Türk doğa ve fen dergisi :/Türk doğa ve fen dergisiVol. 13(3)
Bingöl University (TR), Inonu University (TR)
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu
Openalex Percentile: Top 74%
Remote-Sensing Image Classification
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