Accuracy analysis, dem generation and validation using russian tk-350 stereo-images

TK-350 stereo-scenes of the Zonguldak testfield in the north-west of Turkey have been analysed. The imagery had a base-to-height ratio of 0·52 and covered an area of 200 km × 300 km, with each pixel representing 10 m on the ground. Control points digitised from 1:25 000 scale topographic maps were used in the test. A bundle orientation was executed using the University of Hanover program BLUH and PCI Geomatica OrthoEngine AE software packages. Tests revealed that TK-350 stereo-images can yield 3D geopositioning to an accuracy of about 10 m in planimetry and 17 m in height. A 40 m resolution digital elevation model (DEM) was generated by the PCI system and compared against a reference DEM, which was derived from digitised contour lines provided by 1:25 000 scale topographic maps. This comparison showed that accuracy depends mainly on the surface structure and the slope of the local terrain. Root mean square errors in height were found to be about 27 and 39 m outside and inside forested areas, respectively. The matched DEM demonstrated a systematic shift against the reference DEM visible as an asymmetric shift in the frequency distribution. This is perhaps caused by the presence of vegetation and buildings.     

Analytical methods Of assessing the image quality associated with digital and photographic imaging systems

The introduction of digital cameras for aerial survey photography and use of scanners with processed aerial film present a number of technical questions concerning the way photography is to be acquired in the future. Among the questions to be addressed are the comparative metric properties of images acquired by each system and the associated image quality characteristics. The new digital camera systems will require very careful appraisal, using well-established methods of assessing metric quality already available to survey organisations. The questions concerning image quality are more difficult to answer, as they require very specialised instrumentation if measurements are to be made directly in practice. Over the course of the past several decades a more analytical approach to assessing image quality has emerged, and one that may be used by individuals. The method is particularly effective where information on the micro-image characteristics of products is made available by the manufacturers concerned. An outline is given of some considerations that need to be taken into account when using an analytical approach, with references given for further reading.     

采用DPIV技术研究浅水平板岛屿尾流

人们对于尾流的研究大都针对绕流体在展向非常长的情形,但是在天然环境和水利工程中出现的多为水深相对很浅的流动。由于槽底和自由水面的限制,浅水域中的尾流有着与深水尾流不同的流动规律。采用数字粒子图像测速(DPIV)技术,在长30m、宽3.5m、高1m的水槽中比较系统地量测了浅水中绕平板岛屿的尾流区流场。分析了大尺度旋涡的运动规律,得到了尾流流动形式随尾流稳定性参数的变化规律。目前如此大尺度浅水岛屿尾流的定量实验研究并不多见。     

A New Model for Quantifying Anisotropic Scale Invariance and for Decomposition of Mixing Patterns

A new power–law function has been derived to represent the relationship between area of the set consisting of wave numbers with spectral energy density above S (A(>S)) on the two-dimensional frequency plane and S. The power–law relation holds if the field concerned possessing isotropic scale invariance or generalized scaling invariance involves rotational and ratio-scale changing transforms. The equation is valid for dealing with common exploration geophysical and geochemical fields encountered in mineral exploration and environmental assessment. This power–law function not only provides a new model for characterizing anisotropic scaling invariance for generalized scaling field, for example, estimating the power exponent of power spectrum of generalized scale invariance measure in frequency domain, but also forms a theoretical base for the S–A filtering technique developed for decomposing a mixing field into components on the basis of distinct scaling properties in the frequency domain. It is demonstrated that the method has potential to become a general technique for image processing and pattern recognition.     

概率神经网络与BP网络模型在遥感图像分类中的对比研究

通过分析概率神经网络(以下称PNN)的基本结构及其训练算法,建立了卫星图像分类的概率神经网络模型,并通过实例对比分析了概率神经网络与BP网络分类模型的分类效果。实验表明,PNN图像分类方法在分类精度上优于误差反向传播神经网络模型,且分类时间相当,是一种有效的图像分类方法。     

基于灰度形态学的高分辨率遥感影像预处理

提出了一种从高分辨率遥感影像中提取线性目标时影像预处理的方法。该方法基于灰度形态学的Top-Hat运算和灰度膨胀运算，用Top-Hat算子除去影像的噪声，再利用灰度膨胀增强影像目标和背景之间的对比度，使目标更易于识别。经过处理的遥感影像，能够更有效地提取影像的目标。     

IMD法在多光谱图像分类中的应用

数学形态学着重于分析和处理图像的几何结构信息。根据这一原理，在图像分类预处理过程中，对各种地物区域的几何结构特点进行分析，构造相应的结构元素，然后对图像进行形态迭代分解法(IMD，Iterative Morphological Decompostion)变换。在变换结果中，地物区域的灰度信息进行了归一化处理，同时区域的几何结构特点和独立地物得到了有效保留。将多光谱图像的IMD变换结果进行分类实验的结果表明，该方法可以有效提高多光谱图像分类的精度和效率，具有较强的适用性。     

GIS数据辅助下的线状目标自动提取

首先介绍了遥感影像中线状目标骨架自动提取的意义和研究现状，然后结合老的GIS数据，提出了一种算法来实现遥感影像中线状目标骨架的自动提取，算法主要包括影像预处理、GIS数据与影像的配准、骨架跟踪、编组连接与数据简化等步骤。最后又利用遥感影像和相应的GIS数据进行了实验，实验证明了算法的可行性和有效性。     

图像控制点数据库的设计与实现

地面控制点数据是航天航空图像摄影测量几何处理的必需数据。文中首先比较了控制点数据的存储管理方式，即采用文件系统方式与数据库方式的优缺点；接着分析了控制点图像数据的特征，从而提出了图像控制点数据的数据库存储方案，讨论了图像控制点数据库的查询方法；最后结合文中的方法，设计并且实现了一个控制点图像数据库管理与应用实验系统。通过分析认为，建立控制点图像数据库是重复利用控制点资源的有效途径。     

一种基于DCT变换的盲水印检测算法

提出了一种基于DCT变换的盲图像水印算法。实验表明 ,该算法对典型攻击具有较好的鲁棒性。