整体法与序贯法在测量平差中的比较

讨论了整体法与序贯法在测量平差中的应用,并结合实例比较整体法与序贯法在相同观测情况下的平差结果和精度问题。实例表明:在测量平差中,若测量网中数据较多,并且这些数据是在不同时期所得,用序贯法具有较高的处理效率。     

面向对象分类特征优化选取方法及其应用

与传统基于像元的分类方法比较,面向对象的分类方法可利用的地物信息更加丰富,然而如何从众多信息中筛选出能够有效提取不同地物的分类特征,从而提高分类效率与精度,是使用面向对象方法分类时急需解决的问题。SEaTH算法（分离阈值法）是一种有效的自动选取分类特征并计算阈值的方法,但其只考虑了类间距离,容易存在信息的冗余,从而对分类精度造成一定影响。本文在SEaTH算法的基础上,综合考虑了特征间的相关性、类间距离以及类内距离,对SEaTH算法进行了优化,并将改进前后的两种方法运用到广东省肇庆市TM影像及环境一号卫星影像土地覆盖分类中进行对比分析。实验结果表明,改进后的方法筛选出的特征在提取地物上更为有效,尤其使耕地的分类精度提高了12.26%,使分类总体精度由80%提高到了85.26%。改进后的方法对不易获取多时相影像的地区的土地覆盖分类具有重要意义。     

运用GVF Snake算法提取水域的不规则边界

GVF Snake是一种改进型主动轮廓提取算法。本文在详细介绍GVF Snake原理的基础上,重点对GVF Snake的内、外部约束力在边界提取中的作用以及初始边界对提取结果的影响进行了实验研究,提出了初始边界和内部约束力权值的合理设置方法,设计并实现了交互式GVF Snake算法,并用于提取遥感影像上水域的不规则边界。该算法采用种子点区域生长法自动给出水域的初始边界,采用人机交互法设置内部约束力权值,然后运用GVF Snake算法搜索水域的实际边界。实验表明：对于形状极不规则的水域,交互式GVF Snake算法也能方便、快速、准确地获取其边界。     

基于遗传算法的RBF神经网络在GPS高程拟合中的应用

本文针对RBF神经网络中隐含层径向基中心值的确定,利用遗传算法对其进行优化,并应用于高程拟合的实验研究中。通过将遗传算法优化的RBF神经网络与K-均值优化的RBF神经网络及标准RBF神经网络进行高程拟合的误差对比分析表明:遗传算法优化的RBF神经网络提高了拟合的稳定度,改善了精度。     

PATHCLUST在聚落遗址空间模式研究中的应用

本文主要讨论PATHCLUST算法的原理和方法,给出了聚类分析选择最优算法应注意的问题;以郑州地区仰韶文化聚落遗址空间模式研究为例,讨论了PATHCLUST算法在聚落遗址空间模式研究中的应用。结果表明,此算法可有效揭示聚落遗址的空间分布结构规律。     

A GEOMETRIC ALGORITHM FOR TILTED-CAMERA PERSPECTIVE PROJECTION AND THE COMPARISON WITH EXTERNAL PERSPECTIVE PROJECTION

ABSTRACT

A geometric algorithm for Tilted-Camera Perspective (TCP) projection is proposed in this paper based on the principle of perspective projection. According to that, the difference between TCP projection and External Perspective (EXP) projecton is analyzed. It is put forward prerequisites making these two projections were compatible, and some examples are given.     

Automatic change detection for road networks from images based on GIS

Up to now, detailed strategies and algorithms of automatic change detection for road networks based on GIS have not been discussed. This paper discusses two different strategies of automatic change detection for images with low resolution and high resolution using old GIS data, and presents a buffer detection and tracing algorithm for detecting road from low-resolution images and a new profile tracing algorithm for detecting road from high-resolution images. For feature-level change detection (FL-CD), a so-called buffer detection algorithm is proposed to detect changes of features. Some ideas and algorithms of using GIS prior information and some context information such as substructures of road in high-resolution images to assist road detection and extraction are described in detail.     

The decision of the optimal parameters in Markov random fields of images by genetic algorithm

This paper introduces the principle of genetic algorithm and the basic method of solving Markov random field parameters. Focusing on the shortcomings in present methods, a new method based on genetic algorithms is proposed to solve the parameters in the Markov random field. The detailed procedure is discussed. On the basis of the parameters solved by genetic algorithms, some experiments on classification of aerial images are given. Experimental results show that the proposed method is effective and the classification results are satisfactory.     

Visualization and damage assessment for flooded area

A practical method for visualizing flood area and evaluating damage is presented, which consists of two technical approaches: self-programming and adapting commercial GIS platforms. The low-cost and easy-to-use GIS-Based model developed by self-programming can meet current requirements of most local authorities, especially in developing countries. In this model, two cases, non-source flood and source flood, are distinguished and the Seed-spread algorithm suitable for source-flood is discussed; The flood damage is assessed by overlaying the flood area range with thematic maps and other related social and economic data. and all thematic maps are converted to raster format before overlay analysis. Two measures are taken to improve the operation efficiency of speed seed-spreed algorithm. The accuracy of the model mainly depends on the resolution and precision of the DEM data, and the accuracy of registering all raster layers and the quality of attribute data.     

基于Harris兴趣值的影像线特征高精度提取方法

针对影像高精度线特征提取问题,本文提出一种基于Harris兴趣值的直线提取方法:利用EDISON算法提取影像的初始边缘,并将其细化到单像素,对提取的每一边缘点在其法线方向进行基于Harris兴趣值的子像素定位,并将精确定位后的点拟合成直线.通过采用两幅真实影像进行试验,证实了本文所提方法的有效性.