论发展遥感图像应用智能处理技术

任何对地观测系统获得的原始图像数据实质上都是地球表面电磁波谱特征的综合反映。经地面站系统处 理得到的常规图像产品仍存在大气、地形等多种随机因素导致的几何畸变与辐射失真 , 并且多种地物目标信息混 杂 , 甚至相互迭掩 , 彼此抑制。所以 , 严格地说 , 这些图像只是一种信息源 , 属“数据”范畴 , 必须对其进行再 处理才能得到适应不同专业需要的优质图像和有用信息。至今 , 从事遥感图像处理的科技人员大多出身于电子、计 算机等专业 , 故对于不同地理景观、不同季节、不同传感器所获得的图像数据 (一串灰度数码) , 往往很难体会到 其中包含着的极为丰富而复杂的生物、地学内容。一个能出色完成一般图像处理任务的杰出图像处理专家 , 不一 定能胜任各种不同应用目的所要求的图像处理任务。常常使得海量遥感数据难以得到有效的利用。据此 , 笔者认 为应把遥感图像处理分解为系统处理与应用处理两大类 , 它们是既相互衔接又彼此有别的技术分支。前者只从图 像总体要求出发 , 着眼于改善、提高图像整体质量 ; 后者则必须密切关注具体的应用目的与对象 , 形成融入了地 学分析思路、并精确反映遥感成像机理的图像应用处理技术。文中给出了发展遥感图像应用处理技术的流程框图 , 列举了森林火灾、虫灾监测 , 洪涝灾情快速反应 , 城市扩展 , 低产土壤清查 , 土地利用动态监测等多项任务中的 成功实践。     

基于纹理与分形理论的气象卫星云图目标物识别

气象卫星云图上的目标物进行识别具有重大的实际意义。本文利用计算机图像处理和模式识别技术,结合分形理论对卫星云图上常见的三种云和晴空进行了纹理特征提取,设计神经网络进行了识别实验,结果证明这种方法是有效的。     

夏季选择北太平洋安全航线的方法研究

根据多年平均流场和卫星云图分析,提出了一种夏季北太平洋上中国至北症状,中美洲远洋船舶安全航行的航线选择区,它位于２００ｈＰａ副热带高压脊线附近至其南部对流层上部槽以北广阔地区,并以实例作了较充分讨论。     

Nested plutons as megageopetal structures: The Merrimac plutons,northern Sierra Nevada,California

Contacts within nested plutons are crucial for constraining the relative timing of pluton emplacement and the internal geometry of composite plutons. Exposures in orogenic belts are commonly discontinuous, however, disguising these contacts. In this paper, the Merrimac plutons in the northern Sierra Nevada of California are used as an example of how composition and foliation patterns can allow the definition of unexposed contacts and identify nested plutons. Image analysis techniques were used to determine modal compositions of a total of 52 samples from the Merrimac plutons. The integrated analysis of compositional data and foliations patterns reveals a critical contact within the plutons, and suggests that the Merrimac plutons indicate way-up towards the north-east at the time of emplacement 142 ± 3 Ma ago. This paper provides guidelines for recognizing nested plutons in poorly exposed areas and shows that consistent structural and compositional assymmetries within nested plutons can be used as regional top-direction indicators.     

基于GDAL和NetCDF的影像金字塔构建方法

介绍了GDAL和NetCDF在图像数据处理和栅格数据调度上的帮助和优势,提出了一种新的影像金字塔模型构建方法,从底层开发的关键技术上做了改进优化,提高了影像重采样方法的运行效率,在此研究领域上提供了一定的理论和实践基础。     

SPOT与TM图像的数字复合试验

陆地卫星TM图像含有丰富的光谱信息,SPOT全色波段图像数据分辨率较高,因此,如何将这两种图像数据有效地结合起来,在遥感应用领域中显得越来越重要。本文研究了SPOT和TM图像数据的数字复合方法。结果表明,复合后的图像提高了分辨率,增加了光谱信息。     

Image‐ray Tomography

Seismic tomography is a well‐established approach to invert smooth macro‐velocity models from kinematic parameters, such as traveltimes and their derivatives, which can be directly estimated from data. Tomographic methods differ more with respect to data domains than in the specifications of inverse‐problem solving schemes. Typical examples are stereotomography, which is applied to prestack data and Normal‐Incidence‐Point‐wave tomography, which is applied to common midpoint stacked data. One of the main challenges within the tomographic approach is the reliable estimation of the kinematic attributes from the data that are used in the inversion process. Estimations in the prestack domain (weak and noisy signals), as well as in the post‐stack domain (occurrence of triplications and diffractions leading to numerous conflicting dip situations) may lead to parameter inaccuracies that will adversely impact the resulting velocity models. To overcome the above limitations, a new tomographic procedure applied in the time‐migrated domain is proposed. We call this method Image‐Incident‐Point‐wave tomography. The new scheme can be seen as an alternative to Normal‐Incidence‐Point‐wave tomography. The latter method is based on traveltime attributes associated with normal rays, whereas the Image‐Incidence‐Point‐wave technique is based on the corresponding quantities for the image rays. Compared to Normal‐Incidence‐Point‐wave tomography the proposed method eases the selection of the tomography attributes, which is shown by synthetic and field data examples. Moreover, the method provides a direct way to convert time‐migration velocities into depth‐migration velocities without the need of any Dix‐style inversion.     

基于SIFT特征的SAR图像配准方法在玉树地震中的应用

本文针对SAR图像特点, 提出了基于改进SIFT(尺度不变特征变换)算法的SAR图像配准方案: ① 对待配准图像进行ISEF(无限对称指数滤波器)滤波处理, 降低图像的斑点噪声; ② 采用SIFT算法提取特征点, 略过差分金字塔第一层的特征点检测, 提高时间效率; ③ 在欧氏空间内剔除误匹配点, 提高配准精度。 实验表明, 本文提出的SAR图像配准方案检测到的匹配点对的数量和稳健性都有提高, 精度能够满足亚像元级SAR图像的应用需求, 且用时比传统SIFT方法减少60%以上。 最后对精配准的SAR图像进行震害变化检测, 得到的震害分布与高分辨率光学图像上判读的建筑物毁坏情况基本一致。     

NDVI时间序列在全球耕地提取中的应用

针对全球范围内只能依据单季相Landsat影像数据提取耕地的现状,在现有基于影像光谱与纹理特征的监督分类方法基础上,引入NDVI时间序列数据,解决部分单季相影像造成的耕地与其他类型的混分问题。实验表明,利用NDVI时间序列数据能有效地反映耕地的物候特征,弥补使用单季相Landsat影像提取耕地的缺陷,较好地完善全球耕地的提取方案,提高了耕地提取精度。     

Capabilities of Large-scale Particle Image Velocimetry to characterize shallow free-surface flows

Irrespective of their spatial extent, free-surface shallow flows are challenging measurement environments for most instruments due to the relatively small depths and velocities typically associated with these flows. A promising candidate for enabling measurements in such conditions is Large-scale Particle Image Velocimetry (LSPIV). This technique uses a non-intrusive approach to measure two-dimensional surface velocity fields with high spatial and temporal resolutions. Although there are many publications documenting the successful use of LSPIV in various laboratory and field open-channel flow situations, its performance has not been equally substantiated for measurement in shallow flows. This paper aims at filling in this gap by demonstrating the capabilities of LSPIV to: (a) accurately evaluate complex flow patterns in shallow channel flows; and (b) estimate depth in shallow flows using exclusively LSPIV measurements. The demonstration is provided by LSPIV measurements in three shallow flow laboratory situations with flow depths ranging from 0.05 to 0.31 m. The obtained measurements illustrate the LSPIV flexibility and reliability in measuring velocities in shallow and low-velocity (near-zero) flows. Moreover, the technique is capable to evaluate and map velocity-derived quantities that are difficult to document with alternative measurement techniques (e.g. vorticity and shear stress distributions and mapping of large-scale structure in the body of water).