Detection of small ship targets from an optical remote sensing image

Abstract

Detection of small ships from an optical remote sensing image plays an essential role in military and civilian fields. However, it becomes more difficult if noise dominates. To solve this issue, a method based on a low-level vision model is proposed in this paper. A global channel, high-frequency channel, and low-frequency channel are introduced before applying discrete wavelet transform, and the improved extended contrast sensitivity function is constructed by self-adaptive center-surround contrast energy and a proposed function. The saliency image is achieved by the three-channel process after inverse discrete wavelet transform, whose coefficients are weighted by the improved extended contrast sensitivity function. Experimental results show that the proposed method outperforms all competing methods with higher precision, higher recall, and higher F-score, which are 100.00%, 90.59%, and 97.96%, respectively. Furthermore, our method is robust against noise and has great potential for providing more accurate target detection in engineering applications.

Keywords

small target / saliency / contrast sensitivity

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Acknowledgements

This work was an extended research based on low-level vision model SIM and MCS. We would like to thank Dr. Fang XU and Murray (et al.) for sharing their evaluation codes. This work was supported by Major Projects of the Ministry of Science and Technology (No. 2016YFB0501202) and the Natural Science Foundation of Jilin Province, China (No. 20170101164JC).

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