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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
