基于U-ASPP-Net的北极独立海冰精细识别方法
投稿时间:2021-01-28  修订日期:2021-03-19  点此下载全文
引用本文:
摘要点击次数: 75
全文下载次数: 0
作者单位邮编
郑付强 中国科学院上海技术物理研究所 200083
匡定波 中国科学院上海技术物理研究所 
胡勇 中国科学院上海技术物理研究所 200083
巩彩兰 中国科学院上海技术物理研究所 
黄硕 中国科学院上海技术物理研究所 
李澜 中国科学院上海技术物理研究所 
何志杰 中国科学院上海技术物理研究所 
基金项目:国家重点研发计划(2017YFC0602103)
中文摘要:北极海冰区域独立海冰识别的准确性对于保证航行安全、规划北极航线和动态修正航线具有重要的指导意义。风云三号卫星MERSI-Ⅱ影像的空间分辨率能达到250m,相比SAR影像具有幅宽大、重访周期短、成本低的特点,能够提供大面积的冰情信息,是动态识别北极独立海冰的理想数据源。传统的针对光学遥感数据源的海冰识别方法在一定程度上无法较好地区分独立海冰与碎屑冰、小冰和冰水混合的薄冰区,对边缘以及小块独立海冰的分割效果较差,无法识别薄云覆盖下的独立海冰。为此,基于风云三号卫星MERSI-Ⅱ影像的特性,提出了一种基于U-ASPP-Net的独立海冰分割算法,该算法在U-Net的基础上引入了空洞空间金字塔池化模块和空洞深度可分离卷积构建了新型独立海冰分割网络U-ASPP-Net,并在网络后端将FDWloss作为损失函数,最后利用重叠消边策略生成最终的独立海冰分割图。为验证U-ASPP-Net的准确性与有效性,选取U-Net、Deeplab v3+和分区梯度差分与双峰阈值分割法作为对照方法进行实验,实验结果表明,基于U-ASPP-Net的独立海冰精细化分割方法在OA、Kappa系数、IOU、Dice系数四种指标上均优于其他方法,对细节与边缘的提取能力较强,对极小块海冰的还原度较高。此外,算法在一定程度上能够解决基于中分辨率遥感影像提取独立海冰时无法解决的薄云干扰问题,对薄云下的海冰依然具有良好的提取能力,能够为北极航线的动态规划提供较为准确的技术支持。
中文关键词:北极航线  风云三号卫星  独立海冰  U-ASPP-Net  精细化分割
 
Refined segmentation method based on U-ASPP-Net for Arctic independent sea ice
Abstract:The accuracy of independent sea ice identification in the Arctic sea ice region has important guiding significance for ensuring navigation safety, planning Arctic routes and dynamically correcting routes. The image of FY-3 satellite MERSI II has a spatial resolution of 250m. Compared with SAR image, it has the characteristics of larger size, shorter revisit period and lower cost. As an ideal data source for dynamic identification of isolated Arctic sea ice, it can provide information about the ice conditions over large areas. To some extent, the traditional sea ice identification method based on optical remote sensing data sources are unable to distinguish the thin ice areas mixed with independent sea ice, small ice debris and ice water. Using this method, the segmentation effect on edge and small pieces of independent sea ice is poor, and independent sea ice covered by thin clouds cannot be identified. For this reason, based on the characteristics of the FY-3 MERSI II images, an algorithm of independent sea ice segmentation based on U-ASPP-Net is proposed. The algorithm introduces the Atrous Spatial Pyramid Pooling module and Atrous Depthwise Separable Convolution on the basis of U –Net to develop a new independent sea ice segmentation network U-ASPP-Net. Meanwhile, FDWloss is used as the loss function at the back end of the network. Finally, the overlap elimination strategy is used to generate the final independent sea ice segmentation map. In order to verify the accuracy and effectiveness of U-ASPP-Net, U-Net, Deeplab v3+ and partition gradient difference and bimodal threshold segmentation method are selected as control methods for experiments. The experimental results show that the independent sea-ice fine segmentation method based on U-ASPP-NET is superior to other methods in the four indexes of OA, Kappa coefficient, IOU, Dice coefficient. It has a strong ability to extract details and edges, and has a high degree of reduction to tiny sea ice. In addition, this algorithm can solve the problem of thin cloud interference that cannot be solved when extracting independent sea ice based on medium-resolution remote sensing images to a certain extent. It still has a good ability to extract sea ice under thin clouds and can provide more accurate technical support for the dynamic planning of the Arctic route.
keywords:Arctic route, FY-3 satellite, independent sea ice, U-ASPP-Net, refined segmentation
  HTML  查看/发表评论  下载PDF阅读器

版权所有:《红外与毫米波学报》编辑部