Thermal Infrared Small Ship Detection in Sea Clutter Based on Morphological Reconstruction and Multi-Feature Analysis
| Autor: | Yangfan Huang, Yongsong Li, Bo Li, Zhengzhou Li, Weiqi Xiong, Yong Zhu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Brightness
thermal infrared (TIR) imaging Computer science media_common.quotation_subject ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology Residual 01 natural sciences Structure tensor lcsh:Technology Image (mathematics) small ship target detection saliency detection 010309 optics lcsh:Chemistry multi-feature analysis gray-level morphological reconstruction 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Contrast (vision) General Materials Science Computer vision Closing (morphology) Instrumentation lcsh:QH301-705.5 media_common Fluid Flow and Transfer Processes business.industry sea clutter lcsh:T Process Chemistry and Technology General Engineering lcsh:QC1-999 Computer Science Applications lcsh:Biology (General) lcsh:QD1-999 lcsh:TA1-2040 Clutter 020201 artificial intelligence & image processing Artificial intelligence business lcsh:Engineering (General). Civil engineering (General) Intensity (heat transfer) lcsh:Physics |
| Zdroj: | Applied Sciences, Vol 9, Iss 18, p 3786 (2019) Applied Sciences Volume 9 Issue 18 |
| ISSN: | 2076-3417 |
| Popis: | The existing thermal infrared (TIR) ship detection methods may suffer serious performance degradation in the situation of heavy sea clutter. To cope with this problem, a novel ship detection method based on morphological reconstruction and multi-feature analysis is proposed in this paper. Firstly, the TIR image is processed by opening- or closing-based gray-level morphological reconstruction (GMR) to smooth intricate background clutter while maintaining the intensity, shape, and contour features of ship target. Then, considering the intensity and contrast features, the fused saliency detection strategy including intensity foreground saliency map (IFSM) and brightness contrast saliency map (BCSM) is presented to highlight potential ship targets and suppress sea clutter. After that, an effective contour descriptor namely average eigenvalue measure of structure tensor (STAEM) is designed to characterize candidate ship targets, and the statistical shape knowledge is introduced to identify true ship targets from residual non-ship targets. Finally, the dual method is adopted to simultaneously detect both bright and dark ship targets in TIR image. Extensive experiments show that the proposed method outperforms the compared state-of-the-art methods, especially for infrared images with intricate sea clutter. Moreover, the proposed method can work stably for ship target with unknown brightness, variable quantities, sizes, and shapes. |
| Databáze: | OpenAIRE |
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