面向基元的高空间分辨率矿区遥感影像土地利用分类

为了合理开发矿产资源和有效监测矿区生态环境,采用面向基元的分类方法,对广西横县某矿区的高分辨率航空遥感影像进行了土地利用分类.通过优化分形网络演化多尺度分割方法,高效提取了矿区两个尺度上的影像基元层;基于基元信息,详细分析了各地表地物光谱特征、空间特征以及类相关特征,建立了研究区土地利用的分类知识库;采用决策支持的模糊逻辑推理法进行分类,使分类的精度从53%提高到了90%.表明面向基元的方法能较好地利于高空间分辨率矿区影像的各种特征进行高精度的土地利用分类.      

基于岩土材料层析成像的孔隙网络构建算法

孔隙网络模型是研究多孔介质和其中颗粒的关键。现有的构建孔隙网络模型的算法有许多,但人们开始越来越多地研究基于图像的算法。将讨论一种基于中轴线的孔隙网络构建算法,并且对原有算法中孔隙中心表示方法不合理及缺少中轴线上各点坐标的问题提出改进,改进后的算法提出了孔隙中心的另一种表示方法,并且中轴线上任一点的坐标都被标出。在构建孔隙网络模型后利用该模型计算孔隙体积和喉径,并且针对过度分割的问题提出基于欧氏距离及基于分水岭算法的两种融合算法对孔隙和孔喉进行融合。     

集成空间变换结构与深度残差网络的遥感影像场景分类方法

针对传统高分辨率遥感影像的场景分类效率较低,以及卷积神经网络在遥感影像场景分类上由于空间不变性而导致的分类精度不高的问题,提出了一种结合空间变换网络和迁移学习的高分辨率遥感影像场景分类算法.首先,利用ImageNet数据集训练深度残差网络ResNet101得到预训练模型,通过知识迁移提高模型目标探测效率;之后在模型中嵌入空间变换结构,使模型能够主动在空间上变换特征映射,提高模型的鲁棒性;最后,在模型中添加Dropout层减小模型出现过拟合的概率.本方法在AID和NWPU-RESISC45两种不同规模的高分遥感影像数据集上进行了验证,在只有20%训练样本的情况下仍达到了94.30%和93.63%的分类精度.实验结果表明本次改进模型具有更好的特征提取能力,针对易误分类场景的分类结果更优.     

GIS空间数据索引技术研究与实现

GIS通常包含各种大量的空间信息,空间数据索引的建立有利于提高空间数据的存储、检索效率。因此,对空间数据索引模型的研究具有重要的现实意义。OracleSpatial的R-树和四叉树是索引两种空间数据索引模型和空间数据双层查询模型。在Oracle8i对象关系型的数据库管理系统中,通过空间数据和属性数据的有效结合,利用OracleSpatial提供R-树和四叉树两种空间索引方式,可实现GIS中空间数据索引、检索功能,保证了空间数据查询的快速性和准确性。     

基于完全三叉树堆排序的波前扩展有限差分地震波走时快速算法

波前扩展有限差分地震波走时算法具有物理意义明确、因果稳定性强的特点,但每次波前扩展都要寻找波前面上的最小走时点。当计算网格点数较多,特别是涉及到三维走时计算时,寻找波前面上的最小走时点是一项十分耗时的工作。研究发现,波前扩展有限差分地震波走时算法的波前点具有两个突出特点:①波前点更新十分频繁,通常每次取出波前最小走时点后都要插入若干新的波前点;②新计算出的波前点的走时通常比较大。数据结构中的二叉树堆排序方法可以提高寻找波前面上最小走时点的效率,根据特点①,在原始二叉树堆排序方法的基础上,优化了插入新波前点和移除波前面上最小走时点的流程,实际计算结果表明,与原始的二叉树堆排序方法相比,改进后的二叉树堆排序方法可以提高大约20%的计算效率。根据特点②,将原始的二叉树堆排序方法推广到多叉树,实际计算结果表明,完全三叉树堆排序方法优于二叉树和四叉树堆排序方法,可以再提高5%的计算效率。     

砂样图像岩屑自动分割提取方法

通过将砂样图像进行单颗粒分割,识别砂样成分,可显著提高砂样岩性分析的准确性和效率。现有的砂样图像分割方法主要以传统分水岭算法和卷积神经网络为主,但由于对单颗粒岩屑轮廓细节提取不足,误分割率高。本文提出一种以图像融合算法为桥梁,将卷积神经网络和分水岭算法相结合的单颗粒图像分割提取方法。首先利用改进的Mask R-CNN网络快速分割砂样原图,获得其初分割图像;然后,将初分割图像与砂样原图进行融合,再使用改进的分水岭算法对融合结果进行分割;最后,利用砂样原图坐标点匹配方法,将分水岭分割得到的结果图像进行修正,完成单颗粒岩屑图像提取。实验结果表明,本文的单颗粒自动分割提取方法准确率高达96.77%,且模型更轻量和精准,为岩屑图像分割提供了一种可行且有效的方法,可满足有效测算油藏层构造变化、查找潜在沉积物源及储层动态变化的需求。     

基于GF-1影像多尺度-光谱差异分割的不同喀斯特地貌区土地利用信息提取

影像分割是高分辨率遥感影像信息提取的前提,遥感影像分割的精确程度直接影响遥感分类的精度。为提高喀斯特山区遥感影像信息提取的精度,采用多尺度-光谱差异分割对喀斯特山区高分辨率影像分割,通过标准最近邻分类法提取土地利用信息,对比了仅多尺度分割、多尺度-光谱差异分割两种分割方法下喀斯特山区土地利用信息提取的精度。结果表明:（1）多尺度-光谱差异分割能改善过分割和欠分割现象。（2）多尺度-光谱差异分割优于单一使用多尺度分割。（3）多尺度-光谱差异分割综合了影像的光谱、纹理、形状等特征,进而提高了喀斯特山区影像分割分类的精度。      

一种面向对象的最优分割尺度计算模型

作为信息提取和分类的前提,面向对象的影像分割尺度参数的设置直接影响到提取和分类的精度。本文以GF-2影像数据为例,在已有分割理论和方法的基础上提出一种基于最优分割尺度的计算模型（OS模型）。该模型以主成分分析所得的主成分以及新建的归一化植被指数（normalized vegetation index,NDVI）特征层作为分割参考层,综合考虑均质因子的影响,构建加权尺度评价指数,插值拟合最优分割尺度。构建误差系数（E_c）对模型进行评价,结果表明：OS模型误差系数（E_c=1.15%）小于传统模型（E_c=3.28%）,且分割对象更均匀、与实际地物更接近。     

基于四叉树算法优化检索效率的三维建模技术

三维地质建模是研究如何利用GIS软件将三维空间地质实体真实地再现,实现地质体的三维可视化和相关空间分析,为地质研究和矿产资源勘查提供技术支撑。本文在综合前人研究成果的基础上,对目前常用的基于MapGIS的三维地质建模方法进行了总结,并提出了一种利用四叉树算法优化检索效率的三维建模技术,对于解决城市地质、工程地质、环境地质、三维地质填图中的三维建模问题具有重要意义。     

深部开采上覆岩层采动裂隙网络演化的分形特征研究

借助相似模拟材料模型试验,模拟了在深部开采条件下上覆岩层采动岩体裂隙分布状态,运用分形几何理论研究了采动岩体裂隙网络分形维数随开采宽度、采场矿山压力、岩层沉降的动态演化规律,并分析了断层对采动岩体裂隙网络分布演化的影响以及采动岩体裂隙网络在三带的分布特征。结果表明：随开采宽度增加,采动岩体裂隙网络分形维数呈现总体增大趋势,在断层影响下表现出降维特点;分形维数与超前工作面压力和岩层沉降均具有非线性关系;三带采动岩体裂隙网络均具自相似性,冒落带、裂隙带、弯曲带分形维数比为1.082 3:1.139 4:1。     

基于数字图像分割法的跨孔雷达走时层析成像

跨孔雷达走时层析成像主要利用雷达波的走时进行反演,走时提取的正确与否将直接影响到层析成像的效果。数字图像分割法基于凸集投影（POCS）方法,使用能量比彩色图像分割技术准确提取走时。数字图像分割法提取走时首先应用在折射地震波的数据处理中。笔者首次将数字图像分割法提取走时的方法应用到跨孔雷达走时层析成像中,使用迭代线性反演算法重建了雷达波速度场。反演过程中,使用最小二乘QR分解法（LSQR）求解线性方程组,利用弯曲射线追踪技术构建雅可比矩阵,走时的计算值则由多模板快速推进算法（MSFM）得到。为了验证数字图像分割法在走时层析成像中的效果,使用一组合成数据及一组实测数据分别对比了基于数字图像分割法和基于传统能量比法获得的层析成像反演结果。对比结果表明,使用数字图像分割法得到的层析成像结果更为精确,误差更小,能为判断地下雷达波速度场提供更为有力的帮助。     

An unsupervised multi-scale segmentation method based on automated parameterization

The continuous improvement of the launched satellites’ spatial and spectral resolutions has brought new challenges for remote sensing image segmentation technology. The traditional supervised methods greatly depend on artificial interpretation and reduce the degree of automation and robustness of image segmentation. Therefore, the article proposes a novel unsupervised multi-scale segmentation method for high-resolution remote sensing images based on automated parameterization and it mainly includes three steps, adaptive selection of scale parameter (SP) based on local area homogeneity index J-value, multi-scale segmentation based on the inter-scales boundaries constraint strategy, and region merging based on multi-features. The article makes experiments by multi-group high-resolution remote sensing images of different launched satellites and compares the proposed method with the well-known commercial software eCognition and a traditional supervised method. The results show that the proposed method can locate the object edges more accurately and extract the object outlines more completely, and needs no human intervention in segmentation process, so it can provide a generic and effective unsupervised solution for high-resolution remote sensing image segmentation.     

A new algorithm using image colour system transformation for rock grain segmentation

Summary The present paper is concerned with the development and application of an effective automatic algorithm of image analysis in order to detect grain boundaries on microscope images of Redziny dolostone and Wisniowka quartzite. The algorithm utilises sets of 6 colour images for each measurement field on thin sections, which are recorded using an optical polarizing microscope in different polarization set-ups. The proposed method is based on an image pre-processing procedure that is focused on colour system transformation, followed by rock grain boundaries segmentation using the image analysis methods for each colour image. For the image pre-processing procedure, several colour system transformations were selected and compared. By using the alternative colour systems that concentrate on colour information we are able to minimise the effects of internal micro-structures in the grain boundaries segmentation procedure. The grain boundary maps obtained confirm that the use of an approximately perceptually uniform colour system as an image pre-processing procedure can significantly improve the rock grain segmentation. This newly-developed method may facilitate petrographical and stereological studies of rock structures.     

Fine classification of construction land using high-resolution remote sensing images: a case study in planning restricted zone of nuclear power plant

Detailed construction land information plays a significant role in monitoring planning restricted zone of nuclear power plant and ecological environment protection. This study focuses on developing fine classifying method of construction land in planning restricted zone of nuclear power plant using high spatial resolution GF(GaoFen)-1 remote sensing images. The object-oriented classification method is used in this study; the important process of which is image segmentation and classification. Multi-scale segmentation method, rule-based decision tree, and the nearest neighbor classifier are used in classifying construction land classes, i.e., road, industrial, and residential. An optimal segmentation scale is crucial to image segmentation in object-oriented classification. Instead of laborious trial-and-error experiments for optimal image segmentation, the change rates of the local variance in the homogeneous region are calculated to get the optimal segmentation scales. Multi-level classification strategy is used in the following classification. Rule-based decision tree is used to classify road and water, vegetation and non-vegetation, and industrial and residential. And the nearest neighbor classifier is used to classify cropland and forest within the vegetation land use type. The accuracy assessment result shows that the overall accuracy is 89.67% and Kappa coefficient is 0.85 for object-oriented classification, which is much higher than pixel-based maximum likelihood classifier (overall accuracy is 79.17% and Kappa coefficient is 0.74) and support vector machine classifier (overall accuracy is 74.16% and Kappa coefficient is 0.68).     

Gravel Image Segmentation in Noisy Background Based on Partial Entropy Method

INTRODUCTIONImage thresholding has been widely used in many areas,and there are many methods for thresholding. But it is verydifficult to segmentgravel objects,because of wide variation ingray levels and particle dimensions and the presence of manysmall objects in the background corrupting the image bystationary or white noise. Shannon’s entropy is a concept ininformation theory,which means the more information,theless the entropy value. By m eans of entropy concept,researchers have prop…     

基于面向对象分类的稀土开采区遥感信息提取方法研究

离子吸附型稀土矿是我国宝贵的矿产资源,运用遥感影像分类技术提取稀土开采区可以准确地实现对稀土开采状况的监测,但仅利用光谱信息往往难以保证分类精度。本文以江西寻乌稀土矿区为研究区,以IKONOS影像为数据源,应用面向对象分类方法提取了稀土开采区的遥感信息。针对稀土开采区的分布特点,选择基于边缘的分割算法进行影像分割;结合地形信息、光谱信息及几何信息建立规则集,进行特征提取;最后采用隶属度函数法实现面向对象分类,并与传统的光谱角填图分类进行对比分析。研究结果表明,面向对象分类法提取稀土开采区的总体精度为92.49%,Kappa系数为0.857 6,与传统监督分类方法相比有了很大的提高。     

Automated Segmentation of Resistivity Image Logs Using Wavelet Transform

We describe a wavelet-transform-based method for automated segmentation of resistivity image logs that takes into account the apparent dip in the data and addresses the problem of discriminating lithofacies boundaries from noise and intrafacies variations. Our method can be applied to borehole measurements in general, but might have an advantage when applied to resistivity image logs as it addresses explicitly the large variability in facies segments recorded with a high-resolution multiple-sensor tool. We have developed an algorithm based on this method that might outperform other existing segmentation methods in the cases of low to moderate dip. We made a detailed comparison of the segmentation from our method with the one done by a geologist to delineate different lithofacies blocks in a well drilled in a deepwater depositional environment. Our results show considerable success rates in reproducing the geologically defined lithofacies boundaries, and the generality of our procedure suggests it could also be applied to other depositional environments.     

面向对象的遥感图像分类方法研究

影响遥感图像分类效果的主要因素之一是空间分辨率。通过融合多分辨率遥感图像,引入面向对象的思想,有效地克服了多光谱图像空间分辨率低的问题。该方法由图像分割和分类等一系列技术组成,首先用基于区域分割法则对正射校正SPOT图像进行分割,然后把它作为参考用最大似然法分类器和其他一些经验规则对TM图像进行分类。对土地覆盖图分类进行精度测试,取得了良好的应用效果。