摘要
水体是合成孔径雷达(SAR)图像解译的一类重要内容。针对含水体的SAR图像的成像特点,给出了一种基于轮廓的配准方法。首先,提出了融合观测图像局部统计信息的自适应权马尔科夫随机场(MRF)分割模型,以分割SAR图像水体目标并提取其精确轮廓。然后,提出了轮廓匹配的非均匀高斯混合模型(GMM),该模型能融合轮廓上点的位置信息和以轮廓点为中心的窗口的灰度相似性信息。最后,对含水体目标的SAR图像进行配准实验。结果显示所提出的MRF分割模型能精确地定位目标边缘并保持图像的细节,轮廓匹配的非均匀GMM对噪声、外点及局部变形具有稳健性,能较好地实现含水体目标的SAR图像配准。
Body of water is a kind of important content of synthetic aperture radar （SAR） image interpretation. In this paper, a registration method, which is based on the contours and aiming at the imaging features of SAR image including body of water, is proposed. At first, an adaptive weighting Markov random field （MRF） segmentation model which is integrating local statistical information of observed image is proposed to segment the target of water body of SAR image and accurately extract its contour, Then, a non-uniform Gaussian mixture model （GMM） of contour matching is proposed. The mixture model can integrate both the location information of point of contours and the gray scale similarity information of windows including the contour points as the centers. At last, the registration experiments of SAR image including body of water are conducted. Results show that the proposed MRF segmentation model can accurately locate the edge of object and reserve the details of image. The non-uniform GMM for contours matching is robust to noise, outliers and local deformation, which can achieve the registration of SAR image including body of water better.
出处
《光学学报》
EI
CAS
CSCD
北大核心
2017年第9期295-303,共9页
Acta Optica Sinica
基金
国家自然科学基金青年科学基金(11501436)
陕西省教育厅专项科研计划项目(16JK1326)
西安工程大学博士科研启动基金(BS1420)
关键词
遥感
合成孔径雷达
图像配准
非均匀高斯混合模型
马尔科夫随机场
轮廓
remote sensing
synthetic aperture radar
image registration
non-uniform Gaussian mixture model
Markov random field
contour
