一种基于嫦娥一号CCD影像的影像匹配方法

月球测绘是完成月球探测任务的基础保障。这里提出了一种适合于CE-1获取的CCD影像的多尺度约束自动匹配方法。首先利用SURF算子提取影像上特征点;然后进行基于准核线和最小欧式距离约束的影像匹配;最后采用随机采样算法对误匹配点进行剔除而得到同名点信息。实验结果表明,该匹配方法提取的同名点有利于CE-1月球影像DEM的生成。     

利用多尺度Hough变换提取高分辨率SAR图像建筑物L型结构

提出了一种利用多尺度Hough变换从高分辨率SAR图像提取建筑物L型结构的方法。针对高分辨率SAR图像建筑物L型结构的特点,建立了建筑物L型结构简化几何模型,并采用从粗到精的思路利用多尺度Hough变换提取建筑物L型结构方向线。并提出了一种L型结构组合度函数对提取直线进行编组,确定建筑物L型结构的方向和拐点。最后,采用基于扫描线的方法计算L型结构线宽,得到完整规则的建筑物L型结构。多幅真实机载高分辨率SAR图像实验结果表明,本方法可以有效地提取高分辨率SAR图像建筑物L型结构,提取结果与实际位置吻合较好。     

从激光扫描数据中进行建筑物特征提取研究

提出了一套基于建筑物几何特征的信息挖掘方案,并具体介绍了研究中采用的一些原理、方法与实用算法,从而可以直接从激光扫描数据中提取建筑物的平面外轮廓信息。利用本方案对车载激光扫描系统获取的城市建筑物试验数据进行了具体的处理,并给出了三维建模和可视化表达结果。     

基于特征的城市交通网络非平面数据库的实现

针对基于特征的GIS及交换网络分析对数据结构的要求，着重讨论了如何建立基于交通网络特征的非平面拓扑，以改进地理分层－关系表设计方法及平面图弧段－节点数据结构在交通网络描述中的不足之处，并通过面向对象的方法、动态分段技术和关系表指针操作，结合实例描述了基于完整交通特征的非平面数据库的实现方法。     

Automatic placement of GIS vector map annotation in area feature by long-diagonal

This paper discusses the placement of Chinese annotation from point of view of graphics. Area Feature is classified as simple polygon, complex polygon and special polygon. For simple ones, annotations are placed along the longest edge. For complex ones, firstly the polygon are simplified according to close points, then the longest diagonal is gotten by comparing length, lastly, annotations are placed along long-diagonal. For special ones, the polygon are partitioned into several parts by a certain rule for getting their sub-diagonals, then their annotation are placed by means of the second.     

A fast clonal selection algorithm for feature selection in hyperspectral imagery

Clonal selection feature selection algorithm (CSFS) based on clonal selection algorithm (CSA), a new computational intelligence approach, has been proposed to perform the task of dimensionality reduction in high-dimensional images, and has better performance than traditional feature selection algorithms with more computational costs. In this paper, a fast clonal selection feature selection algorithm (FCSFS) for hyperspectral imagery is proposed to improve the convergence rate by using Cauchy mutation instead of non-uniform mutation as the primary immune operator. Two experiments are performed to evaluate the performance of the proposed algorithm in comparison with CSFS using hyperspectral remote sensing imagery acquired by the pushbroom hyperspectral imager (PHI) and the airborne visible/infrared imaging spectrometer (AVIRIS), respectively. Experimental results demonstrate that the FCSFS converges faster than CSFS, hence providing an effective new option for dimensionality reduction of hyperspectral remote sensing imagery.     

粗精匹配结合的矢量道路辅助惯性导航算法

针对无源环境下无法采用卫星导航定位方式对惯性导航系统的累积误差进行修正的问题,提出一种采用高精度的矢量道路数据进行粗精匹配的导航校正算法。该方法首先通过分析惯导轨迹的特征标示点以及外接矩形,剔除明显的误匹配道路和冗余道路,获取待匹配道路集合;进而,结合ICCP算法具有匹配精度较高,匹配结果较稳定的优点,完成惯导轨迹位置误差的补偿和校正;最后,根据匹配方差和历史匹配轨迹对匹配结果的准确性进行分析和判断。仿真实验结果表明,该算法能够提高惯性导航定位误差的校正精度,减少在复杂道路交叉口等情况的误匹配。     

Road condition assessment by OBIA and feature selection techniques using very high-resolution WorldView-2 imagery

Accurate information on the conditions of road asphalt is necessary for economic development and transportation management. In this study, object-based image analysis (OBIA) rule-sets are proposed based on feature selection technique to extract road asphalt conditions (good and poor) using WorldView-2 (WV-2) satellite data. Different feature selection techniques, including support vector machine (SVM), random forest (RF) and chi-square (CHI) are evaluated to indicate the most effective algorithm to identify the best set of OBIA attributes (spatial, spectral, textural and colour). The chi-square algorithm outperformed SVM and RF techniques. The classification result based on CHI algorithm achieved an overall accuracy of 83.19% for the training image (first site). Furthermore, the proposed model was used to examine its performance in different areas; and it achieved accuracy levels of 83.44, 87.80 and 80.26% for the different selected areas. Therefore, the selected method can be potentially useful for detecting road conditions based on WV-2 images.     

基于SIFT特征的多源遥感影像自动匹配方法

本文提出一种基于SIFT特征的不同源遥感影像自动匹配方法。首先利用Harris算子结合SIFT特征提取影像上均匀分布的特征点,建立高维SIFT特征描述符;然后以待匹配点与参考点间的欧氏距离为相似性测度,实施两种不同源遥感影像的特征匹配;最后将SIFT特征匹配结果作为初始值,采用将搜索范围扩大到尺度空间后的改进最小二乘影像匹配方法对SIFT特征匹配获得的同名像点进行精匹配。经对同一地区SPOT-5 HRG全色影像与航空摄影影像的匹配试验,取得了较好的结果。     

一种纹理特征融合分类算法

分别利用多通道Gabor滤波器和马尔可夫随机场模型对纹理图像进行分析,得到两组特征影像。将上述两组特征影像进行融合,最后利用融合后的数据实现图像的分类。实验证明,基于上述方法的纹理特征融合分类算法大大提高了图像的分类精度。