| 基于G0分布的SAR图像水边线提取方法 |
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| 引用本文： | 赵泉华,胡广臣,李玉.基于G0分布的SAR图像水边线提取方法[J].地理科学,2017,37(7):1120-1126. |
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| 作者姓名： | 赵泉华 胡广臣 李玉 |
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| 作者单位： | 辽宁工程技术大学测绘与地理科学学院遥感科学与应用研究所,辽宁 阜新 123000 |
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| 基金项目： | 国家自然科学基金（41301479、41271435）、辽宁省自然科学基金（2015020090） |
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| 摘 要： | 为了更加精准地从合成孔径雷达（SAR）图像中提取水边线,提出基于G0分布的SAR图像水边线提取方法。首先,将SAR图像域划分为大小相等的子块,并假设每个子块内像素强度服从独立同一的G0分布;利用矩估计方法得到对应每个子块的粗糙度和散射性参数;根据设定的参数阈值,可划分出粗略的水域,并确定该区域的几何中心;以该几何中心为圆心,向四周做射线,保留经过陆地区域的射线;利用似然函数确定每条射线上的水-陆分界点,依次连接分界点,进而实现SAR图像水边线提取。采用本文方法,分别对模拟和真实SAR图像进行水边线提取实验。定性和定量结果表明：采用基于G0分布的SAR图像水边线提取方法能够有效地克服斑点噪声的影响。
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| 关 键 词： | 水边线提取 G0分布 SAR图像 斑点噪声 |
| 收稿时间： | 2016-09-20 |
| 修稿时间： | 2016-11-26 |
G0 Distribution Based on Water Line Extraction from SAR Image |
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| Quanhua Zhao,Guangchen Hu,Yu Li.G0 Distribution Based on Water Line Extraction from SAR Image[J].Scientia Geographica Sinica,2017,37(7):1120-1126. |
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| Authors: | Quanhua Zhao Guangchen Hu Yu Li |
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| Institution: | Institute for Remote Sensing Science and Application, School of Geomatics, Liaoning Technical University, Fuxin 123000, Liaoning, China |
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| Abstract: | The water line is the demarcation line between land and sea areas. It is important interaction zone for global ecosystem conservation. As a result, it is vital that the rapid, accurate, real-time extraction of water line. Remote sensing solutions using Synthetic Aperture Radar (SAR) are playing an increasingly important role in monitoring water line and have getted much more attention from scholars and related department around the world. The sensor has two types: satellite SAR and airborne SAR. Satellite SAR has many advantages, for instance wide range observation, timely data available and all weather operation. As a result, it is a most suitable sensor for monitoring water line in marine environments. At present, the commonly used satellite SAR sensors for this purpose including Seasat SAR, Jers-1 SAR, Sentinel-1 SAR, and so on. In the SAR images, water line usually shows the edge characteristic, so the edge detection based algorithms are the most commonly used in coastline extraction. The classical edge detection operators including Canny operator, Sobel operator, Roberts operator, Prewitt operator and Laplacian operator, and so on. The operators have some advantages such as simple, fast speed, but they always effected by speckle noise inherent in SAR images, as a result, they can not obtain accurate water line results. So noise is a major issue for the task of boundary detection by the SAR images. Instead of combating the noise, we use a technique for boundary detection in SAR images based on the statistical properties of speckled data. The G0 distribution is a special form of G model, its parameters are very sensitive to the surface roughness and succeeds in characterizing a wide range of areas as sea, mountain chain and urban areas in speckled images. And the parameters required for boundary detection is extracted with moment estimation. Moreover, relative to G distribution, G0 distribution does not include the complex Bessel function, and is a kind of simple statistical distribution model with less parameter. According to the estimated parameters of G0 distribution, the marine and land areas can accurately be separated. In order to extract the water linefrom SAR image, a G0 distribution based algorithm is proposed in the article. First, the domain of SAR image is divided into a set of sub-blocks with the same size, and the grayscales of pixels in each sub-block are assumed to be identical and independent G0 distribution. The roughness of each sub-block and scatter shot parameters of the distribution are obtained with moment estimation. By thresholding the roughness parameter, the rough sea area can be divided, and then its geometric center is determined. On the rays started at the geometrical center, the cut-off points between sea and land are located with likelihood function. Consequently, the water line is formed by linking all the cut-off points. To prove its feasibility, a process of water line extraction has been tested with simulated and real SAR images by the method. Qualitative and quantitative results show that the proposed method can extract water line from SAR image effectively and efficiently. |
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| Keywords: | water line extraction G0 distribution Synthetic Aperture Radar image speckle |
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