Ship detection based on Radarsat-2 full-polarimetric images
Feature extraction is very important when processing the polarimetric synthetic aperture radar (SAR) image, and the key of ship detection. In order to enhance the contrast of ships and clutter, we investigate a new detection parameter (DP) for ship detection based on feature vector with three parameters: span value, the smallest eigenvalue and the combination of entropy and anisotropy, which have the highest TCR (Target- Clutter Ratio) when compared with other parameters after analyzing the Radarsat-2 full-polarimetric SLC data in our experiment. The results show that DP is very effective to enhance the TCR of the image and discriminate all the ships from the background ocean correctly and completely.
ship detection polarimetric SAR feature extraction eigenvalue-decomposition
Wu Bingjie Wang Chao Zhang Bo Wu Fan
Center for Earth Observation and Digital Earth, CAS, Beijing 100094 Graduate University of the Chine Center for Earth Observation and Digital Earth, CAS, Beijing 100094
国际会议
2011 IEEE CIE International Conference on Radar(2011年IEEE国际雷达会议RADAR 2011)
成都
英文
634-637
2011-10-24（万方平台首次上网日期，不代表论文的发表时间）