Detection of ocean internal waves based on Faster R-CNN in SAR images  

作　　者：BAO Sude MENG Junmin SUN Lina LIU Yongxin 

机构地区：[1]Inner Mongolia University,Hohhot 010021,China [2]First Institute of Oceanography,Ministry of Natural Resources,Qingdao 266061,China

出　　处：《Journal of Oceanology and Limnology》2020年第1期55-63,共9页海洋湖沼学报（英文）

基　　金：Supported by the National Natural Science Foundation of China(No.61471136);the Special Project for Global Change and Air-sea Interaction of Ministry of Natural Resources(No.GASI-02-SCS-YGST2-04);the Chinese Association of Ocean Mineral Resources R&D(No.DY135-E2-4)

摘　　要：Ocean internal waves appear as irregular bright and dark stripes on synthetic aperture radar(SAR)remote sensing images.Ocean internal waves detection in SAR images consequently constituted a difficult and popular research topic.In this paper,ocean internal waves are detected in SAR images by employing the faster regions with convolutional neural network features(Faster R-CNN)framework;for this purpose,888 internal wave samples are utilized to train the convolutional network and identify internal waves.The experimental results demonstrate a 94.78%recognition rate for internal waves,and the average detection speed is 0.22 s/image.In addition,the detection results of internal wave samples under different conditions are analyzed.This paper lays a foundation for detecting ocean internal waves using convolutional neural networks.Ocean internal waves appear as irregular bright and dark stripes on synthetic aperture radar(SAR) remote sensing images. Ocean internal waves detection in SAR images consequently constituted a difficult and popular research topic. In this paper, ocean internal waves are detected in SAR images by employing the faster regions with convolutional neural network features(Faster R-CNN) framework; for this purpose, 888 internal wave samples are utilized to train the convolutional network and identify internal waves. The experimental results demonstrate a 94.78% recognition rate for internal waves, and the average detection speed is 0.22 s/image. In addition, the detection results of internal wave samples under dif ferent conditions are analyzed. This paper lays a foundation for detecting ocean internal waves using convolutional neural networks.

关 键 词：ocean internal waves FASTER regions with convolutional NEURAL NETWORK features (Faster R-CNN) convolutional NEURAL NETWORK synthetic APERTURE radar (SAR) image region proposal NETWORK (RPN) 

分 类 号：TN9[电子电信—信息与通信工程]