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多传感器卫星图像的配准技术研究
其他题名Study on Automatic Registration of Multi-Sensor Satellite Images
张朝晖
学位类型工学博士
导师马颂德
2003-11-01
学位授予单位中国科学院研究生院
学位授予地点中国科学院自动化研究所
学位专业模式识别与智能系统
关键词多传感器图像配准 形状矩阵 Nljrbs参数化描述 智能剪刀 滤波 信息熵 水体提取 Multi-sensor Image Registration Shape Matrix Nurbs Filter Intelligent Scissor Empirical Entropy Water Body Extraction
摘要图像配准技术在机器视觉、模式识别、医学图像分析、遥感图像处理等诸多 领域中的研究热点。本文在分析与探讨多源卫星图像配准技术难点的基础上, 结合项目的应用背景,确定以EFRS SAR图像及SP0T-P光学卫星图像为研究对象, 以多传感器卫星图像配准技术的研究作为本文工作重点,相关工作及主要贡献 如下:1.图像的滤波。针对SAR图像斑点噪声抑制,对目前国际上较为流行的滤波方 法进行分析,提出了一种基于修正Frost核的滤波算法,该算法综合考虑滤波窗 口的局部统计信息,既充分保留了图像的细节,又克服了增强型Frost滤波器过 多保留假"细节"的缺陷,在噪声抑制与细节保持方面取得了一个较好的折衷。 2.水体特征的提取。针对水域在SAR图像与光学图像中灰度分布具有弱随机性 的特点,提出了一种基于信息熵的水体提取方法,利用信息熵,将灰度图像映 射为熵值图像,采用单阂值方法能有效地提取熵值图像中呈现暗区的水域;为 了准确确定水体的边界,结合边缘检测信息,本文给出了基于模板的水体边界 提取方案。 3.多传感器卫星图像精细化配准技术的研究。基于雷达图像与光学图像的区 域特征和参数化描述边缘特征,本文提出了一种多传感器图像的精细化配准方 法。在粗匹配阶段,本文融合了形状矩阵的形状相似统一度量准则、形状矩阵 的长半径方向信息、以及PCA的主方向信息,通过形状相似准则与方向一致准 则的约束,从而有效地避免了区域匹配的多义性。在精匹配阶段,利用边缘特 征的NURBS 曲线参数化描述,有效地解决了由于斑点噪声而产生的SAR图像"不 规则"边缘问题,而且利用NIJRBS曲线的局部可控性,有效地解决了由于图像 获取条件或成像时间差异而造成图像对应特征局部变化对特征匹配的不良影响 问题,利用距离准则、曲率准则以及方向准则等的约束,找到对应NLIRBS曲线 的匹配控制点对,并利用NLJRBS曲线在仿射变换下控制点的不变性,实现两图 像问的精匹配。 4.针对大范围图像配准,本文从图像中特征丰富的局部区域配准入手,提出 了一种基于局部区域配准模型的自适应扩展方案,进而实现大图像或图像中特 征稀疏区域的配准;在此基础上,通过大图像中其它部分少量匹配点修正变换 模型,从而达到改善图像配准质量的目的。
其他摘要Image registration is a research focus in many fields such as computer vision, pattern recognition, medical image analysis and remote sensing image processing, etc. Starting with a brief overview of existing registration techniques for multi-source remote sensing data, we focus on the study of automatic registration of multi-sensor satellite images especially for SAR and optical data. The related work and main contributions are summarized as follows: 1. Image filtering. Based on an analytical review of several kinds of image filters, a new method is proposed for SAR de-speckling. The filter kernel is a modified version of Frost one, which combines the statistical information from the pixel and its neighbor pixels within the filter window. Therefore, the method not only avoids over-smoothing of SAR image structural details, but also amends the deficiency of keeping "false edges" by the enhanced Frost filter. So it makes a good trade off between speckle filtering and details preserving. 2. Feature Extraction. With the assumption that water bodies hold weak radiometric randomness in both SAR and optical remote sensing images, based on information theory, we propose a method for water body extraction. By means of empirical entropy, the gray level image is mapped into entropy image where dark areas correspond to water ones. Water areas can therefore be extracted by means of threshold technique and some post-processing. In order to get a more accurate border of water bodies, we also present a template-based scheme for border detection by combining the template and edge information. 3. Multi-sensor satellite image registration. Based on multi-layer feature matching, a coarse-to-fine registration procedure is proposed. In the stage of coarse registration, area features are depicted by shape matrix, which provides a unified measure rule not only for shape similarity but also the orientation consistency of this shape. Further the local orientation consistency, which is described by both Principle Component Analysis (PCA) and the shape matrix, effectively avoids the ambiguity of shape matching. In the stage of registration refinement, the parameterized description of edge features by NURBS curves properly solves the "irregular edge "problem because of speckle noise in SAR images. The utilization of local controllability of NURBS curve overcomes the local deformation, which is caused by the terrain or environmental change due to the different acquisition conditions of images. By combining some constraints on two corresponding edges, such as distance constraint, orientation constraint, etc. we obtain the matched control points of NURBS curves, which are invariant under affine transformation. The registration refinement can therefore be realized. 4. For the registration of large area images, an adaptive propagati
馆藏号XWLW848
其他标识符848
语种中文
文献类型学位论文
条目标识符http://ir.ia.ac.cn/handle/173211/5789
专题毕业生_博士学位论文
推荐引用方式
GB/T 7714
张朝晖. 多传感器卫星图像的配准技术研究[D]. 中国科学院自动化研究所. 中国科学院研究生院,2003.
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