| Title | A Target Detection Method in SAR Images Based on Superpixel Segmentation |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Liu, Ming, Chen, Shichao, Lu, Fugang, Xing, Mengdao, Wei, Jingbiao |
| Conference Name | 2020 IEEE 3rd International Conference on Electronic Information and Communication Technology (ICEICT) |
| Date Published | Nov. 2020 |
| Publisher | IEEE |
| ISBN Number | 978-1-7281-9045-7 |
| Keywords | composability, Conferences, constant false alarm rate (CFAR), cyber physical systems, Detectors, False Data Detection, Human Behavior, human factors, image segmentation, information and communication technology, object detection, pubcrawl, Radar polarimetry, resilience, Resiliency, superpixel segmentation, synthetic aperture radar, synthetic aperture radar (SAR) images, target detection |
| Abstract | A synthetic aperture radar (SAR) target detection method based on the fusion of multiscale superpixel segmentations is proposed in this paper. SAR images are segmented between land and sea firstly by using superpixel technology in different scales. Secondly, image segmentation results together with the constant false alarm rate (CFAR) detection result are coalesced. Finally, target detection is realized by fusing different scale results. The effectiveness of the proposed algorithm is tested on Sentinel-1A data. |
| URL | https://ieeexplore.ieee.org/document/9334216 |
| DOI | 10.1109/ICEICT51264.2020.9334216 |
| Citation Key | liu_target_2020 |
A Target Detection Method in SAR Images Based on Superpixel Segmentation