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Open AccessArticle

Ship Detection in Optical Remote Sensing Images Based on Wavelet Transform and Multi-Level False Alarm Identification

by Fang Xu 1,2, Jinghong Liu 1,*, Chao Dong 1,2 and Xuan Wang 1
1
Changchun Institute of Optics, Fine Mechanics and Physics, Key Laboratory of Airborne Optical Imaging and Measurement, Chinese Academy of Sciences, Changchun 130033, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2017, 9(10), 985; https://doi.org/10.3390/rs9100985
Received: 10 July 2017 / Revised: 18 September 2017 / Accepted: 20 September 2017 / Published: 22 September 2017
(This article belongs to the Special Issue Instruments and Methods for Ocean Observation and Monitoring)
Ship detection by Unmanned Airborne Vehicles (UAVs) and satellites plays an important role in a spectrum of related military and civil applications. To improve the detection efficiency, accuracy, and speed, a novel ship detection method from coarse to fine is presented. Ship targets are viewed as uncommon regions in the sea background caused by the differences in colors, textures, shapes, or other factors. Inspired by this fact, a global saliency model is constructed based on high-frequency coefficients of the multi-scale and multi-direction wavelet decomposition, which can characterize different feature information from edge to texture of the input image. To further reduce the false alarms, a new and effective multi-level discrimination method is designed based on the improved entropy and pixel distribution, which is robust against the interferences introduced by islands, coastlines, clouds, and shadows. The experimental results on optical remote sensing images validate that the presented saliency model outperforms the comparative models in terms of the area under the receiver operating characteristic curves core and the accuracy in the images with different sizes. After the target identification, the locations and the number of the ships in various sizes and colors can be detected accurately and fast with high robustness. View Full-Text
Keywords: remote sensing; ship detection; wavelet transform; the improved entropy; pixel distribution remote sensing; ship detection; wavelet transform; the improved entropy; pixel distribution
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MDPI and ACS Style

Xu, F.; Liu, J.; Dong, C.; Wang, X. Ship Detection in Optical Remote Sensing Images Based on Wavelet Transform and Multi-Level False Alarm Identification. Remote Sens. 2017, 9, 985.

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