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1.
Hyperion高光谱影像的分析与处理 总被引：4，自引：1，他引：3
EO-1 Hyperion是新型地球观测卫星,也是一颗实验性的高光谱星载卫星.Hyperion影像具有高光谱分辨率的特点,同时该传感器在波段的辐射定标参数、影像的坏线和条带、以及光谱的Smile效应等处理方面有待改进.针对黑河上游祁连山区的Hyperion影像,进行了DN值分析,DN值转换辐亮度值、影像条带去除和坏线替换、光谱Smile效应校正,以及经MODTRAN辐射传输的大气订正等处理,获得了高光谱分辨率的雪反射率的反演网像,为研究区积雪面积的提取、雪粒径和雪反照率的反演等后续工作提供了基础图像. 相似文献
2.
Spectral unmixing estimates the abundance of each endmember at every pixel of a hyperspectral image. Each material in traditional unmixing algorithms is represented through a constant spectral signature. However, endmember variability always exists due to environmental, atmospheric, and temporal conditions, which leads to poor accuracy of the estimated abundances. This paper proposes a new unmixing algorithm based on a new linear transformation called endmember orthonormal mapping (EOM) to overcome the aforementioned problem. The EOM transformation maps original spectral space to a new EOM space to reduce endmember variability. In the original spectral space, each material is represented by a set of spectra (endmember set) which is extracted using the automated endmember bundles (AEB) method. The EOM transforms each endmember set to a vector in the EOM space so that these vectors are orthonormal. On account of orthonormalized endmembers, the condition number of the mixing matrix in the EOM space reduces. Furthermore, we consider the noise term as an additional virtual endmember set mapped to a vector that is orthogonal to other endmembers. As a result, a promising unmixing accuracy is obtained through applying the least squares abundance estimation in the subspace orthogonal to noise. Experimental results of both synthetic and real hyperspectral images demonstrate that the proposed algorithms provide much enhanced performance compared with the state-of-the-art algorithms. 相似文献
3.
高光谱遥感图像受到成像系统硬件限制,无法同时具有高空间分辨率和高光谱分辨率,较低的空间分辨率制约高光谱图像的应用,超分辨率重建技术可提高图像的空间分辨率。针对高光谱图像的超分辨率重建中光谱保真度的问题,在重建方法中耦合光谱保真度函数,结合结构自适应归一化卷积方法,提出基于光谱保真约束的归一化卷积方法。具体地,将图像局部邻域内像素间的光谱相关性作为约束条件,将与中心像素光谱类似的像素赋予较大权值,从而提高重建后图像光谱特性的保持程度。实验中分别从空间结构与光谱信息保真两个方面来评价重建后结果,结果表明该方法具有较好的光谱信息保持度。 相似文献
4.
Krishnendu Banerjee Manish Kumar Jain 《Journal of the Geological Society of India》2018,91(2):239-247
This work illustrates the effectiveness of hyperspectal image spectroscopy and lab spectroscopy in identification techniques of minerals in alteration zone of ore body. The adopted procedure involves testing of Hyperion image spectra, their processing for noise, spectral matching and spectral similarity measurement with selected library spectra. Average weighted spectral similarity; visual and statistical matching techniques were used to select end-members from image spectra. Minimum noise fraction and pixel purity index technique were used to retrieve end-member spectra from hyperion image. Hyperspectral image like hyperion has the capability to deliver laboratory standard spectroscopic result. This paper illustrates the capability of hyperion image spectra in copper ore identification and mapping of chalcopyrite outcrop. A systematic approach has been made in this paper. This approach describes how image end member spectra and laboratory spectra can be co-related to fetch accurate spectral form of chalcopyrite ores. Thus, statistical and graphical comparison has been carried out between image derived end member spectra and laboratory spectra of chalcopyrite for better accuracy. The visual measurements is satisfactory, R = 0.973 for fine and 0.976 for medium grained chalcopyrite ore. Excellent statistical significance levels (90–97%) are found while comparing these spectra. There are many success stories of sub-pixel and N-dimensional feature space methods to separate the hydrothermal alteration zones from iron oxide mixed ore bodies. Thus, unmixing methods are very useful for mapping of most dominating mineral parts of a pixel from hyperspectral images which have coarse spatial resolution. Finally, mapping of mineralized zone has been achieved through sub-pixel based classifiers like spectral angle mapper (SAM), constrained energy minimization (CEM) and adaptive coherence estimator (ACE) techniques. 相似文献
5.
This article addresses a new reserve estimation method which uses fuzzy modeling algorithms and estimates the reserve parameters
based on spatial variability. The proposed fuzzy modeling approach has three stages: (1) Structure identification and preliminary
clustering, (2) Variogram analysis, and (3) Clustering based rule system. A new clustering index approach and a new spatial
measure function (point semimadogram) are proposed in the paper. The developed methodology uses spatial variability in each
step and takes the fuzzy rules from input-output data. The model has been tested using both simulated and real data sets.
The performance evaluation indicates that the new methodology can be applied in reserve estimation and similar modeling problems 相似文献
6.
Pravesh Debba Emmanuel J. M. Carranza Alfred Stein Freek D. van der Meer 《Mathematical Geosciences》2009,41(4):421-446
This paper describes a quantitative methodology for deriving optimal exploration target zones based on a probabilistic mineral
prospectivity map. The methodology is demonstrated in the Rodalquilar mineral district in Spain. A subset of known occurrences
of mineral deposits of the type sought was considered discovered and then used as training data, and a map of distances to
faults/fractures and three band ratio images of hyperspectral data were used as layers of spatial evidence in weights-of-evidence
(WofE) modeling of mineral prospectivity in the study area. A derived posterior probability map of mineral deposit occurrence
showing non-violation of the conditional independence assumption and having the highest prediction rate was then put into
an objective function in simulated annealing in order to derive a set of optimal exploration focal points. Each optimal exploration
focal point represents a pixel or location within a circular neighborhood of pixels with high posterior probability of mineral
deposit occurrence. Buffering of each optimal exploration focal point, based on proximity analysis, resulted in optimal exploration
target zones. Many of these target zones coincided spatially with at least one occurrence of mineral deposit of the type sought
in the subset of cross-validation (i.e., presumed undiscovered) mineral deposits of the type sought. The results of the study
showed the usefulness of the proposed methodology for objective delineation of optimal exploration target zones based on a
probabilistic mineral prospectivity map. 相似文献
7.
遥感图像异常识别是遥感应用领域一个颇受关注的研究课题,在军事目标识别和自然环境保护等许多领域都有潜在应用价值。不妨假设遥感图像背景像素分布于随空间位置缓慢变化的一系列高斯超椭球体内,异常像素则分布于超椭球体之外。在这种假设前提下,首先应用Weiszfeld方法估算遥感图像中一系列高斯超椭球体的重心和波段协方差矩阵;然后,计算各像素到对应的超椭球体重心的马氏距离,并用直方图法确定马氏距离的异常下限;最后,把马氏距离高于异常下限的像素作为异常像素识别出来。在GDAL遥感图像数据输入输出函数库基础上,用VC++语言开发了遥感图像像素级异常识别的算法程序;用美国亚特兰大TM图像进行了方法的应用实验研究。结果表明,该方法对遥感图像中的局部异常具有很好的识别效果。 相似文献
8.
Airborne imaging spectrometer (also known as hyperspectral) remote sensing has been widely used to characterize mineralogy on mine waste surfaces, which is useful for predicting potential sources of acidity and metal leaching. The most successful applications employ fine spatial resolution—20-m pixels or smaller. Future satellite imaging spectrometer sensors are proposed to provide coarser spatial resolution—30- to 60-m pixels. This study examined the ability to map minerals related to acid mine drainage with visible to shortwave infrared hyperspectral imagery at varying spatial scales (2-, 15-, 30-, 60-m pixels) at the Leviathan mine Superfund site, located in the Eastern Sierra Nevada. Mineral maps were produced using spectral angle mapper and matched filtering algorithms. The 15-m images provided comparable maps to the 2-m images. The 30- and 60-m images lost the ability to identify smaller features; however, they were still able to identify high- and low-priority remediation zones at least 75 m in width. Based on our results, we believe 30-m spatial resolution on a satellite hyperspectral sensor will be sufficient for identifying hazardous surfaces at larger mine waste sites and provide important reconnaissance information that can help prioritize detailed ground-based studies. 相似文献
9.
依据油砂中烃类的微渗漏和油砂组分光谱特征响应原理,利用Hyperion高光谱影像提取和识别与油砂分布相关的波谱信息,进行非常规油气能源--油砂分布的有利区预测。根据油砂所致烃类微渗漏的地表特征可知,低植被覆盖区的异常以矿物异常为主,中、高植被覆盖区的异常以植被异常为主。利用归一化植被指数表征地表植被的不同覆盖程度：当其值为[0.0,0.4）时,采用SAM（spectral angle method）提取矿物异常信息;当值为[0.4,0.7]和（0.7,1.0]时,分别采用LIC（lichenthaler index）和CTR（carter indices）方法提取植被异常信息。同时,为确保提取的矿物和植被异常信息的产生是由油砂中烃类的微渗漏所导致,以野外油砂反射光谱为端元,运用光谱角分类方法提取油砂信息,并将其与获取的矿物和植被异常信息进一步应用空间叠置分析确定油砂分布有利区。结果表明,综合运用野外实测高光谱数据和高光谱影像数据能够较准确地预测出研究区中油砂的分布位置。因此,应用高光谱影像进行油砂分布的有利区预测,可为未来利用遥感技术深入研究油砂可采储量评价提供参考依据。 相似文献
10.
Fatiha Laoufi Ahmed-Hafid Belbachir Noureddine Benabadji Abdelouahab Zanoun 《Comptes Rendus Geoscience》2011,343(10):653-663
We have mapped the region of Oran, Algeria, using multispectral remote sensing with different resolutions. For the identification of objects on the ground using their spectral signatures, two methods were applied to images from SPOT, LANDSAT, IRS-1 C and ASTER. The first one is called Base Rule method (BR method) and is based on a set of rules that must be met at each pixel in the different bands reflectance calibrated and henceforth it is assigned to a given class. The construction of these rules is based on the spectral profiles of popular classes in the scene studied. The second one is called Spectral Angle Mapper method (SAM method) and is based on the direct calculation of the spectral angle between the target vector representing the spectral profile of the desired class and the pixel vector whose components are numbered accounts in the different bands of the calibrated image reflectance. This new method was performed using PCSATWIN software developed by our own laboratory LAAR. After collecting a library of spectral signatures with multiple libraries, a detailed study of the principles and physical processes that can influence the spectral signature has been conducted. The final goal is to establish the range of variation of a spectral profile of a well-defined class and therefore to get precise bases for spectral rules. From the results we have obtained, we find that the supervised classification of these pixels by BR method derived from spectral signatures reduces the uncertainty associated with identifying objects by enhancing significantly the percentage of correct classification with very distinct classes. 相似文献
11.
基于像元基元、极化合成孔径雷达（Synthetic Aperture Radar,SAR）数据和传统机器学习算法的岩性分类方法,易受SAR图像固有斑点噪声影响,精度不高.为了降低噪声的影响,本研究以大尺度像元邻域为基元,用于表征地表地质体的遥感图像特征和岩性语义信息;采用高分三号双极化SAR数据进行极化分解构建3通道假彩色合成影像;然后采用深度卷积神经网络（Deep Convolutional Neural Network,DCNN）迁移学习的方法,提取有效的深度特征表示,分别实现5 m和15 m两种空间分辨率下岩性遥感自动分类.结果表明:基于不同分辨率数据和不同DCNN算法,岩性遥感自动分类的总精度均大于80%,最高精度达到91%.基于大尺度像元邻域和DCNN迁移学习方法,能够实现基于SAR数据的高精度岩性分类. 相似文献
12.
为了在缺少地面实测数据的情况下对遥感油气异常结果进行验证, 利用多光谱遥感数据和高光谱遥感数据对同一地区进行油气异常解译, 针对同一位置使用两种不同数据的异常结果进行相互验证.并提出了利用高光谱异常提取结果作为先验知识的多光谱异常主分量阈值确定方法, 将该方法与传统主分量阈值方法提取的异常结果, 分别与高光谱提取出的粘土异常区域结果进行重叠率计算, 发现该方法提取出的异常区与高光谱提取的结果重叠率达98.808%, 高于传统主分量阈值方法的98.198%.结果表明利用该方法确定的阈值划分出的异常区具有较高的精度. 相似文献
13.
This paper present the results of a study made to assess the grades of iron ore deposits in parts of Noamundi area using the hyperspectral image data (EO-1 Hyperion). The study involves hyperspectral image data, preprocessing (removal of atmospheric effects), spectral curve generation from the image, extraction of certain spectral parameters and spectral data analysis. Atmospheric correction was carried out by using algorithms involving atmospheric analysis of spectral hyper-cubes and Quick Atmospheric Correction modules. Spectral curves generated for the pixels that contain iron ores resemble the spectral signature of iron ores, i.e., very strong absorption at 850–900nm region is observed. The strength of the absorption varies spatially at different pixels. Hence, spectral parameters such as radius of curvature of NIR absorption trough (750–1000nm), position of NIR absorption trough and distance from a reference(100% reflectance) line have been derived for all the image-derived spectra and were compared with the concentration of iron in the ore samples of mines. Empirical models were generated by relating the image-derived spectral parameters of iron ore locations and geochemistry of the samples collected from the same location which shows a reasonable match. Strong negative correlation is seen between the radius of curvature of the NIR absorption trough and concentration of iron with a R2 value of 0.809. The position of the NIR absorption trough is seen to shift towards longer wavelengths with decreasing iron content and the distance from the reference line increases with increasing iron content. Thus, this study indicates that it is feasible to discriminate the grades of iron ores from the spectral parameters derived from Hyperspectral satellite images. 相似文献
14.
Imaging spectrometry for geological remote sensing 总被引：2，自引：0，他引：2
Without use of imaging spectrometry, imaging of the Earth's surface from aircraft and from spacecraft is hampered by the low spectral resolution and limited number of spectral bands, typically less than 10 bands of 100 to 200 nm width. Imaging spectrometry in remote sensing concerns the acquisition of image data in many narrow (< 40 nm wide) contiguous spectral bands with the ultimate goal of producing detailed spectral reflectance curves for each pixel in the image. Many minerals and rocks have unique spectral signatures with characteristic absorption features that are 20 to 40 nm wide. Imaging spectrometers allow to depict these narrow features and thus map surface mineralogy based on spectral image characterization. This paper gives a review of imaging spectrometry and addresses the following topics: airborne and spaceborne systems available, spectral and geometric data pre-processing, atmospheric correction, techniques for thematic data analysis, and applications in the field of geological remote sensing. In the final section a case study is described where imaging spectrometer data is used for mapping surface mineralogy in a hydrothermal alteration system, thus guiding gold exploration. 相似文献
15.
V. R. S. Mani 《Journal of the Geological Society of India》2018,91(5):541-546
With the availability of multi sensor data in many fields, such as remote sensing, medical imaging or machine vision, sensor fusion has emerged as a new and promising research area. It is possible to have several images of the same scene providing different information although the scene is the same. This is because each image has been captured with a different sensor. A non-negative matrix factorization (NNMF) un mixing based fusion technique with vertex component analysis (VCA) based end member initialization and simple multiplicative update to improve the spatial resolution and to preserve the spectral resolution of the hyper spectral image is proposed. Its performance is analyzed with different number of iterations and end member initializations. A Constrained Non Negative Matrix Factorization unmixing based fusion technique is developed by adding a regularization term to the objective function to preserve the spectral resolution of the hyper spectral image, and its performance is analyzed with different number of iterations and end members. A rank two NNMF and hierarchical clustering based end member initialization and block principal pivoting algorithm based abundance estimation technique, for fusing hyper spectral image and simulated multispectral image is proposed and its performance is analyzed for different overlapping and non overlapping group of multispectral and hyper spectral bands. The performance of the above three methods are compared and analyzed. The obtained results show that the performance of rank two NNMF hierarchical clustering based fusion technique is better than the other two constrained and unconstrained NNMF un mixing based techniques. Also, the performance of these three proposed multi sensor image fusion techniques are compared with an existing image fusion technique. 相似文献
16.
高光谱遥感影像分类是高光谱遥感影像处理和应用的重要组成部分。然而,高光谱遥感影像具有波段数量较多和空间分辨率较高等特点,给分类任务带来一定的挑战。为了提高分类精度,充分利用影像的空间信息和像素间的局部信息,提出一种引导滤波联合局部判别嵌入的高光谱影像分类方法。首先,对高光谱遥感影像进行归一化,利用主成分分析方法实现特征提取,将提取的第一主成分影像作为引导图像;其次,采用引导滤波分别提取各波段影像的空间特征;然后,将提取的空间影像特征进行叠加,通过局部Fisher判别分析完成低维嵌入;最后,将得到的低维嵌入特征输入支持向量机分类器得到分类结果。采用Indian Pines和Pavia University两幅高光谱影像进行实验的结果表明：在分别从各类地物中随机选取10%和100个样本作为训练样本的情况下,其总体分类精度分别提高到98.28%和99.45%;对比其他相关方法,该方法能够获取更高的分类精度。该方法在低维嵌入的同时,有效利用了影像的空间信息,改善了分类效果。 相似文献
17.
Experimental comparison of support vector machines with random forests for hyperspectral image land cover classification 总被引：1，自引：0，他引：1
The performances of regular support vector machines and random forests are experimentally compared for hyperspectral imaging land cover classification. Special characteristics of hyperspectral imaging dataset present diverse processing problems to be resolved under robust mathematical formalisms such as image classification. As a result, pixel purity index algorithm is used to obtain endmember spectral responses from Indiana pine hyperspectral image dataset. The generalized reduced gradient optimization algorithm is thereafter executed on the research data to estimate fractional abundances in the hyperspectral image and thereby obtain the numeric values for land cover classification. The Waikato environment for knowledge analysis (WEKA) data mining framework is selected as a tool to carry out the classification process by using support vector machines and random forests classifiers. Results show that performance of support vector machines is comparable to that of random forests. This study makes a positive contribution to the problem of land cover classification by exploring generalized reduced gradient method, support vector machines, and random forests to improve producer accuracy and overall classification accuracy. The performance comparison of these classifiers is valuable for a decision maker to consider tradeoffs in method accuracy versus method complexity. 相似文献
18.
高光谱数据处理及其在广西苗儿山地区的地质应用研究 总被引：8，自引：0，他引：8
本文以广西苗儿山地区机载成像细分红外高光谱数据为例,探讨了高光谱数据的特点及其处理方法。编制了一系列进行数据预处理的软件,进行了条带去除、波段间配准、航向压缩、镜向变换、辐射校正、正切校正、相对反射率转换等预处理,获得了高质量图像。在ＥＮＶＩ软件基础上建立了研究区野外实测光谱曲线库及分类子库,并对各子库进行了系统研究。同时,提出了正确的配准方案,对图像进行了精校正和镶嵌,取得了满意的镶嵌图像;在纯净像元提取、混合像元分解、匹配滤波、光谱特征拟合等方面进行了探索。最后,探讨了高光谱数据的地质应用潜力,尤其在硅化带识别方面取得了成功的效果,发现了一系列新的含铀硅化断裂带;预测了３片成矿有利地段,经验证,在其中两片地区找到了明显的铀偏高和矿化显示。 相似文献
19.
不透水面遥感提取及应用研究进展 总被引：4，自引：0，他引：4
不透水面信息的提取方法与应用是近年来城市规划、热岛效应分析、水环境监测和水资源管理等诸多领域的研究热点.遥感技术的发展使不透水面快速准确提取成为可能.从影像特征(光谱、空间几何、时间)选择、分类器(参数、非参数)选择和空间尺度(像元、亚像元尺度)选择3个方面归纳和总结了各种不透水面遥感提取方法原理、应用现状和存在问题,回顾了不透水面在城市化监测、人口估计、水环境监测、热岛效应分析、水文气候建模分析等领域的应用,指出了不透水面遥感提取和应用的发展方向. 相似文献