一种基于紫外极光图像的亚暴膨胀期起始时刻的自动检测方法   总被引：1，自引：1，他引：0       下载免费PDF全文

杨秋菊  梁继民  刘俊明  胡泽骏  胡红桥 《地球物理学报》2013,56(5):1435-1447

准确界定亚暴起始时刻是理解亚暴相关问题的关键.已有研究主要集中在两方面:一是从极光图像中人工挑选亚暴事件进行案例分析或统计分析来研究亚暴发生机制及亚暴期间的地磁环境;二是基于一些空间物理参数,如AE指数、SME(SuperMAG electrojet)指数、Pi2、正弯扰等,采用人眼判断或是模式识别的方法从中找出亚暴起始时刻.本文尝试采用模式识别的方法从紫外极光图像中自动地检测出亚暴膨胀期起始时刻.首先,将紫外极光图像通过网格化处理转换到磁地方时-地磁纬度(MLT-MLAT)直角坐标下,然后通过模糊c均值聚类方法提取亮斑,再考察亮斑强度是否增强、面积是否极向膨胀来判断是不是亚暴事件.本文方法在1996年12月-1997年2月这三个月的Polar卫星紫外极光图像上进行了实验验证.我们将检测到的亚暴起始时刻与Liou(J. Geophys. Res., 2010, 115: A12219)的人工标记进行了对比,并详细分析了与标记不一致的多检和漏检事件.本文提出的自动检测方法可以快速地从海量紫外极光图像中完成亚暴事件的初步筛选,方便研究人员进一步深入研究极光亚暴.  相似文献   

A comparative data-fusion analysis of multi-sensor satellite images     

《International Journal of Digital Earth》2013,6(8):671-687

Remote-sensing data play an important role in extracting information with the help of various sensors having different spectral, spatial and temporal resolutions. Therefore, data fusion, which merges images of different spatial and spectral resolutions, plays an important role in information extraction. This research investigates quality-assessment methods of multisensor (synthetic aperture radar [SAR] and optical) data fusion. In the analysis, three SAR data-sets from different sensors (RADARSAT-1, ALOS-PALSAR and ENVISAT-ASAR) and optical data from SPOT-2 were used. Although the PALSAR and the RADARSAT-1 images have the same resolutions and polarisations, images are gathered in different frequencies (L and C bands, respectively). The ASAR sensor also has C-band radar, but with lower (25 m) resolution. Since the frequency is a key factor for penetration depth, it is thought that the use of different SAR data might give interesting results as an output. This study describes a comparative study of multisensor fusion methods, namely the intensity-hue-saturation, Ehlers, and Brovey techniques, by using different statistical analysis techniques, namely the bias of mean, correlation coefficient, standard deviation difference and universal image quality index methods. The results reveal that Ehlers' method is superior to the others in terms of spectral and statistical fidelity.  相似文献   

Cartographically Wordy but not Necessarily Worthy     

《The Cartographic journal》2013,50(3):195-197

Abstract

A novel method called multidirectional visibility index (MVI) has been developed and verified. The MVI improves standard cartographic analytical shading with a number of enhancements to topographic detail and prominent structures, i.e. the portrayal of flat areas in lighter tones, the accentuation of morphologic edges, and the multiscale visualisation of morphologic terrain features. The procedure requires a digital elevation model (DEM) and involves the following steps: visibility mask computation; the respective multidirectional altering of the azimuth and elevation angle; the generation of continuous grid MVIs that indicate upper/lower views, quasi-slope, and relative relief; and an appropriate visualisation of the relevant MVI as a standalone technique or in combination with standard hill-shaded relief. The modelling parameters are robust and therefore highly adaptive to different landforms.  相似文献   

A modified stochastic neighbor embedding for multi-feature dimension reduction of remote sensing images     

《ISPRS Journal of Photogrammetry and Remote Sensing》2013

In automated remote sensing based image analysis, it is important to consider the multiple features of a certain pixel, such as the spectral signature, morphological property, and shape feature, in both the spatial and spectral domains, to improve the classification accuracy. Therefore, it is essential to consider the complementary properties of the different features and combine them in order to obtain an accurate classification rate. In this paper, we introduce a modified stochastic neighbor embedding (MSNE) algorithm for multiple features dimension reduction (DR) under a probability preserving projection framework. For each feature, a probability distribution is constructed based on t-distributed stochastic neighbor embedding (t-SNE), and we then alternately solve t-SNE and learn the optimal combination coefficients for different features in the proposed multiple features DR optimization. Compared with conventional remote sensing image DR strategies, the suggested algorithm utilizes both the spatial and spectral features of a pixel to achieve a physically meaningful low-dimensional feature representation for the subsequent classification, by automatically learning a combination coefficient for each feature. The classification results using hyperspectral remote sensing images (HSI) show that MSNE can effectively improve RS image classification performance.  相似文献   

Clustering based on eigenspace transformation – CBEST for efficient classification     

《ISPRS Journal of Photogrammetry and Remote Sensing》2013

Large remote sensing datasets, that either cover large areas or have high spatial resolution, are often a burden of information mining for scientific studies. Here, we present an approach that conducts clustering after gray-level vector reduction. In this manner, the speed of clustering can be considerably improved. The approach features applying eigenspace transformation to the dataset followed by compressing the data in the eigenspace and storing them in coded matrices and vectors. The clustering process takes the advantage of the reduced size of the compressed data and thus reduces computational complexity. We name this approach Clustering Based on Eigen-space Transformation (CBEST). In our experiment with a subscene of Landsat Thematic Mapper (TM) imagery, CBEST was found to be able to improve speed considerably over conventional K-means as the volume of data to be clustered increases. We assessed information loss and several other factors. In addition, we evaluated the effectiveness of CBEST in mapping land cover/use with the same image that was acquired over Guangzhou City, South China and an AVIRIS hyperspectral image over Cappocanoe County, Indiana. Using reference data we assessed the accuracies for both CBEST and conventional K-means and we found that the CBEST was not negatively affected by information loss during compression in practice. We discussed potential applications of the fast clustering algorithm in dealing with large datasets in remote sensing studies.  相似文献   

基于高分辨率SAR图像成像机理的震害信息分析   总被引：2，自引：0，他引：2  

刘金玉  张景发  刘国林 《国土资源遥感》2013,25(3)

与中低分辨率SAR图像相比,高分辨率SAR图像受目标复杂性和成像噪声等因素的干扰更为严重,致使应用高分辨率SAR图像检测震害目标变得更加困难.传统的适用于中低分辨率SAR图像的震害信息提取方法对于高分辨率SAR图像有一定的局限性.为了从高分辨率SAR图像中更加准确地提取震害信息,从SAR图像成像机理和目标的后向散射特征出发,对建筑物和道路、桥梁的震害特征进行了细致分析,为寻求合适的目标检测和提取方法提供了思路.  相似文献   

遥感影像面向对象信息提取技术在GIS土地管理中的应用     

颜士威  曹云刚  雒根雄  王亚飞 《测绘科学》2013,38(1):93-95

本文主要研究通过高分辨率遥感影像和eCognition软件,利用面向对象信息提取技术来获取村庄尺度土地利用类型空间数据的技术方法。本项研究中的实验区主要地物包括麦田、旱作物、荒地、苗圃、道路、水体、建设用地和树木等类型。通过设置不同的分割参数并目视判定待识别地类的轮廓分割效果,获取适用于村庄尺度土地利用类型分类的最优分割参数,并通过分类精度对比说明面向对象信息提取相对于传统分类方法的巨大优势。  相似文献   

基于暗原色的航空遥感影像薄雾去除与改进     

赵桂华  邹晓亮  戴晨光  方勇  陈虹  万欢 《测绘科学》2013,38(1):29-32

本文对航空遥感影像的薄雾进行了研究,根据雾图像成像模型和基于暗原色先验知识,结合图像对比度的自适应调整,提出了一种对航空遥感影像薄雾去除的改进算法。采用数字航空相机DSS439获取的不同地物特征类型的应急遥感影像进行去雾实验,并对实验结果进行分析、比较与评价,验证了该方法的正确性和有效性。  相似文献   

警用地理信息平台中三维全景系统建设研究     

向煜  唐德彬  易佳  张建  白宝玉 《测绘信息与工程》2013,(6):14-18

针对当前警用地理信息平台中空间信息表达直观性欠缺的缺憾,提出了三维全景系统的解决方案。结合警用地理信息平台建设的要求,简述了三维全景技术的原理,详细介绍了在PGIS平台中三维全景系统的系统构架、数据体系、系统功能等,并探讨了系统实现的关键技术。通过实际应用,验证了系统建设的合理性和可操作性,为各地公安三维全景系统的建设提供了较好的参考和借鉴。  相似文献   

基于改进SIFT算法的视频图像序列自动拼接     

卢斌  宋夫华 《测绘科学》2013,38(1):23-25

本文提出了一种自适应帧采样和限定特征提取区域的拼接方法,根据帧间重叠率和帧间隔建立线性模型,并把各帧图像对准到其前后的关键帧上。在特征点提取方面,提出了一种改进的SIFT算法进行特征点提取,并采用随机采用一致性(RANSAC)方法来更新匹配点,在图像融合中采用线性加权渐入渐出的自然融合算法。实验结果表明:该方法对一般场景能稳定的抽取到关键帧,并进行拼接,取得了较好的拼接效果。  相似文献