期刊
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
卷 5, 期 4, 页码 635-648出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIV.2020.2991955
关键词
Infrared imaging; image segmentation; maritime surveillance; target detection
类别
资金
- China Scholarship Council [201606570006]
This paper addresses a problem on infrared maritime target detection robustly in various situations. Its main contribution is to improve the infrared maritime target detection accuracy in different backgrounds, for various targets, using multiple infrared wave bands. The accuracy and the computational time of traditional infrared maritime searching systems are improved by our proposed Local Peak Singularity Measurement (LPSM)-Based Image Enhancement and Grayscale Distribution Curve Shift Binarization (GDCSB)-Based Target Segmentation. The first part uses LPSM to quantize the local singularity of each peak. Additionally, an enhancement map (EM) is generated based on the quantitative local singularity. After multiplying the original image by the EM, targets can be enhanced and the background will be suppressed. The second part of GDCSB-Based Target Segmentation calculates the desired threshold by cyclic shift of the grayscale distribution curve (GDC) of the enhanced image. After binarizing the enhanced image, real targets can be segmented from the image background. To verify the proposed algorithm, experiments based on 13,625 infrared maritime images and five comparison algorithms were conducted. Results show that the proposed algorithm has solid performance in strong and weak background clutters, different wave bands, different maritime targets, etc.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据