Abstract
The edges in infrared image will cause false alarms in small target detection. So a novel edge-preserving background estimation method is proposed in this paper for single frame small target detection. First, we propose a novel background estimation method based on semi-supervised learning, and the Graph Laplacian regularization is utilized in this model to preserve accurate edges in estimated background image. Then, the bilateral kernel is utilized to realize background estimation method. At last, edge-preserving estimated background is eliminated from original image to get difference image which is used as foreground to detect the small target. The experiment results demonstrate that our proposed method can achieve edge-preserving background estimation significantly and efficiently, and get better small target detection results.
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.
