| LIU Meijie,DAI Yongshou,ZHANG Jie,ZHANG Xi,MENG Junmin,XIE Qinchuan.PCA-based sea-ice image fusion of optical data by HIS transform and SAR data by wavelet transform[J].Acta Oceanologica Sinica,2015,34(3):59-67 |
| 基于小波变换和HIS变换的海冰SAR与光学遥感影像融合方法研究 |
| PCA-based sea-ice image fusion of optical data by HIS transform and SAR data by wavelet transform |
| 投稿时间：2014-07-02 修订日期：2014-10-11 |
| DOI：10.1007/s13131-015-0634-7 |
| 中文关键词: 海冰 光学遥感影像 SAR遥感影像 HIS变换 小波变换 PCA方法 |
| 英文关键词:sea ice optical remote sensing image SAR remote sensing image HIS transform wavelet transform PCA method |
| 基金项目: |
| 作者 | 单位 | E-mail | | 刘眉洁 | China University of Petroleum (Huadong), Qingdao 266580, China
First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China
Qingdao University, Qingdao 266071, China | | | 戴永寿 | China University of Petroleum (Huadong), Qingdao 266580, China | daiys@upc.edu.cn | | 张杰 | First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China | | | 张晰 | First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China | | | 孟俊敏 | First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China | | | 谢钦川 | First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China | |
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| 中文摘要: |
| 中国渤海的海冰作为一种自然灾害,其监测和研究引起了广泛关注,已经成为中国海洋管理部门的常规工作。现今,遥感是海冰研究的主要手段,其中合成孔径雷达(Synthetic Aperture Radar,SAR)和光学传感器承担了很重要的监测任务。光学影像能够获取丰富的海冰多光谱信息,SAR影像包含了丰富的海冰纹理信息,如能将两者的优势融合到一起,将会极大地提高海冰监测能力。因而,本文提出了一种海冰光学和SAR影像融合的方法,用以改善海冰识别能力。本文用到的变换和融合方法都是根据海冰光学和SAR影像的自身特点选取的。现有研究结果表明SAR纹理信息在海冰类型识别中能起到很重要的作用。Haar小波变换适用于提取海冰SAR纹理信息,利用此变换可以从ENVISAT ASAR(Advanced Synthetic Aperture Radar)影像中提取海冰SAR纹理信息。根据本文对海冰光学影像的分析发现,色调-强度-饱和度(hue-intensity-saturation,HIS)空间能够比红-绿-蓝(red-green-blue,RGB)空间更好地反映不同海冰类型的光谱特性。因而将中巴资源卫星的(the China-Brazil Earth Resources Satellite,CBERS-2B)光学影像从RGB空间转换到HIS空间。主成分分析(the principal component analysis,PCA)融合方法能够使融合影像最大程度的包含海冰SAR纹理信息和HIS光学信息。融合影像能够吸收海冰SAR和光学影像各自的优势。文中利用客观、主观和综合等三种方法评价了本文提出的融合方法。评价结果表明本文的融合方法能够提高海冰影像的解译和类型识别能力。 |
| 英文摘要: |
| Sea ice as a disaster has recently attracted a great deal of attention in China. Its monitoring has become a routine task for the maritime sector. Remote sensing, which depends mainly on SAR and optical sensors, has become the primary means for sea-ice research. Optical images contain abundant sea-ice multi-spectral information, whereas SAR images contain rich sea-ice texture information. If the characteristic advantages of SAR and optical images could be combined for sea-ice study, the ability of sea-ice monitoring would be improved. In this study, in accordance with the characteristics of sea-ice SAR and optical images, the transformation and fusion methods for these images were chosen. Also, a fusion method of optical and SAR images was proposed in order to improve sea-ice identification. Texture information can play an important role in sea-ice classification. Haar wavelet transformation was found to be suitable for the sea-ice SAR images, and the texture information of the sea-ice SAR image from Advanced Synthetic Aperture Radar (ASAR) loaded on ENVISAT was documented. The results of our studies showed that, the optical images in the hue-intensity-saturation (HIS) space could reflect the spectral characteristics of the sea-ice types more efficiently than in the red-green-blue (RGB) space, and the optical image from the China-Brazil Earth Resources Satellite (CBERS-02B) was transferred from the RGB space to the HIS space. The principal component analysis (PCA) method could potentially contain the maximum information of the sea-ice images by fusing the HIS and texture images. The fusion image was obtained by a PCA method, which included the advantages of both the sea-ice SAR image and the optical image. To validate the fusion method, three methods were used to evaluate the fused image, i.e., objective, subjective, and comprehensive evaluations. It was concluded that the fusion method proposed could improve the ability of image interpretation and sea-ice identification. |
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