各向异性正则化的多帧遥感图像盲复原算法

在大气湍流较强时,一般的遥感图像复原算法难以取得较好的复原效果。针对这种情况,提出了一种基于各向异性约束的多帧遥感图像盲复原算法。该算法不需要成像过程的先验信息,仅根据图像及点扩散函数的非负约束和支持域约束,即可得到较好的复原结果;同时该算法能够自适应地调整正则化参数,在实现图像复原的同时,保持边缘并抑制噪声。试验结果验证了该算法的良好性能,复原后图像的质量得到较大提高。     

利用横向切片进行地物三维重建

提出了一种基于横向切片的地物可量测性三维重构方法,利用平面单应变换和未标定的多视图完成三维重建。通过对重构物体成像进行轮廓约束及场景约束,假设一组平行平面切割重构地物,通过单应变换得到切片的轮廓线构成物体的形状,进而恢复各层轮廓线的三维值,并加入参考高度,求得重构物体的高度。实验证明了此方法对规则与不规则物体的重建均有效,使得整个三维的求解过程具有可测量性。     

断层图象层厚减薄的图家处理方法

本文全面讨论了断层图象层厚减薄的数字图出处理方法──断层间插值技术．详细介绍了现有的灰度插值和形状插值的思路、功能、实现步骤和优缺点．提出了深入研究的目标．     

甘肃疏勒河断裂中段核废物处置库稳定性研究

本文利用遥感图像解译、地质调研和物探等技术手段，对甘肃疏勒河断裂带中段的地质特征及其稳定性进行了研究。通过研究，对疏勒河断裂带的认识有了新的进展，取得了较好的效果。     

遥感技术在泥石流灾害勘查中的应用

本文以具体实例总结和列举了利用遥感图像进行泥石灾害调查的多种应用方法，通过这些方法，不仅对泥石流特征，泥石流灾害，暴发周期和规模做了深层次的解译和研究，而且获得了丰富的调查成果，总结了北京地区泥石流分布规律，活动特点及危害状况，本文还对遥感技术在21世纪地质灾害工作的应用做了简单论述。     

由双目序列影像解求运动参数的非立体匹配方法

在无需实现精确立体匹配的条件下，导出了由双目序列影像得到的双目影像光流场严密解算空间物体运动参数的数学模型，并从理论上分析了该模型的稳健性，同时给出了简单的验证算例。     

遥感图像因子分析的环境意义

本文是一份实验和理论分析报告。六种地理环境类型的遥感图像用因子分析算法作了处理。并介绍了图像因素和Tasseled Cap空间基之间的关系。一般来说第一因素矢量和SB最相似,而第二因素矢量和GV最相似。但在平原农业环境出现相反的结果。 为分析实验的成果,我们试图从理论上进行探讨。假设地面地理特征是一个二维零均值的平稳随机过程,IFOV卷积效应使初级环境景观因子信号被增强,而二级环境因子相对地在传感器的观察下是递降的。 在第二步工作中,发展了一种基于环境景观学概念的方法,它相当于图像处理的奇异值分解(SVD变换),它将用来处理遥感图像的环境信息。     

Satellite sensor modeling and 3D geo-positioning using empirical models

The need for the use of general empirical mathematical models for satellite sensor modeling and 3D geo-positioning has increased recently, mainly because of the absence of the satellite sensor information of some of the high-resolution satellites. In addition, empirical mathematical models can be applied to different satellite sensors since they are time independent mathematical models and do not require specialized commercial software packages. This paper discusses the applicability of the empirical mathematical models presented by the 3D affine model and the 3D polynomial models for satellite sensor modeling and 3D geo-positioning. The objectives of the paper are to demonstrate that (a) the 3D affine model and its modifications of the 3D polynomial models are applicable to different satellite sensors and different types of terrain, and (b) under some conditions, the empirical models can produce accuracies close to those from rigorous mathematical models.     

Updating land cover automatically based on change detection using satellite images: case study of national forests in Southern California

Observing dynamic change patterns and higher-order complexities from remotely sensed images is warranted, but the main challenges include image inconsistency, plant phenological differences, weather variations, and difficulties of incorporating natural conditions into automatic image processing. In this study, we proposed a new algorithm and demonstrated it by producing 2002–2008 and 2010 land-cover maps in heterogeneous Southern California based on an existing 2009 land-cover map. The new algorithm improves the baseline land-cover map quality by discarding potential bad land-cover pixels and dividing each land-cover type into several subclasses. Time series Landsat images were used to detect changed and unchanged areas between baseline year and target year t. Subsequently, for each individual year t, each pixel that was identified as unchanged inherited the baseline classification. Otherwise, each pixel in the changed areas was classified by a similar surrogate majority classifier. The demonstration results in Southern California showed that the land-cover temporal pattern captured the observed successional stages of the ecosystem very well. The accuracy assessment had an overall classification accuracies ranging from 81% to 86% and overall kappa coefficients ranging from 0.79 to 0.83.     

深度图像分割的城市区域倾斜影像密集匹配点云滤波算法

倾斜摄影测量作为一个新兴领域发展势头迅猛,在众多领域得到了广泛应用。但倾斜影像密集匹配点云处理技术研究却相对较少。倾斜影像密集匹配点云分布不均匀、表面粗糙,因而传统的激光扫描点云处理算法在用于倾斜影像密集匹配点云处理时的适用性较低。本文从倾斜影像密集匹配点云特点出发,提出了一种利用点云高程信息生成深度图像提取建筑物非连通区域,在全局范围选取种子点实现多种子点区域生长的点云快速滤波算法。实验结果表明,该算法滤波效果好、速度快,可以改善密集匹配点云部分地物底部边缘不清晰引起错分和区域生长无法分割建筑物非连通区域的问题。