Superpixel-Level CFAR Detectors for Ship Detection in SAR Imagery

被引：148

作者：

Pappas, Odysseas ^{[1
]}

Achim, Alin ^{[1
]}

Bull, David ^{[1
]}

机构：

[1] Univ Bristol, Visual Informat Lab, Bristol BS8 1TH, Avon, England

来源：

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS | 2018年 / 15卷 / 09期

基金：

英国工程与自然科学研究理事会;

关键词：

Constant false alarm rate (CFAR); ship detection; superpixels (SPs); synthetic aperture radar (SAR); TARGETS;

D O I：

10.1109/LGRS.2018.2838263

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

Synthetic aperture radar (SAR) is one of the most widely employed remote sensing modalities for large-scale monitoring of maritime activity. Ship detection in SAR images is a challenging task due to inherent speckle, discernible sea clutter, and the little exploitable shape information the targets present. Constant false alarm rate (CFAR) detectors, utilizing various sea clutter statistical models and thresholding schemes, are near ubiquitous in the literature. Very few of the proposed CFAR variants deviate from the classical CFAR topology; this letter proposes a modified topology, utilizing superpixels (SPs) in lieu of rectangular sliding windows to define CFAR guardbands and background. The aim is to achieve better target exclusion from the background band and reduced false detections. The performance of this modified SP-CFAR algorithm is demonstrated on TerraSAR-X and SENTINEL-1 images, achieving superior results in comparison to classical CFAR for various background distributions.

引用

页码：1397 / 1401

页数：5

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