共查询到20条相似文献，搜索用时 966 毫秒
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介绍了MAP方法的基本原理,建立了适用于高光谱影像增强的观测模型,给出了模型的代价函数.在假设高光谱影像像点相互独立的条件下,给出了代价函数的求解方法,分析并给出了基于MAP的高光谱影像增强流程.利用PHI高光谱影像及其对应的高分辨率全色影像数据,进行了MAP高光谱影像增强实验.实验结果的定量分析表明,本文方法能够在保... 相似文献
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高光谱图像处理与信息提取前沿 总被引：2，自引：0，他引：2
高光谱遥感是对地观测的重要手段,高光谱图像处理与信息提取技术则是高光谱遥感领域的核心研究内容之一。本文简要介绍了高光谱遥感的主要特点,系统梳理了高光谱图像处理与信息提取面临的关键问题和主要研究方向,在此基础上,从噪声评估与数据降维方法、混合像元分解方法、图像分类方法、目标探测与异常探测方法等4个方面对高光谱图像处理与信息提取的理论发展过程和最新前沿进展进行了综述。另外,还对高光谱图像处理与信息提取中的高性能处理技术进行了总结和分析。未来,伴随着智能化信息分析和高性能硬件处理技术发展,高光谱遥感卫星系统也将步入智能化时代。针对这一趋势,本文指出高光谱图像处理与信息提取方法要注重多学科交叉,充分利用机器学习、人工智能等领域的新成果;要重视软硬件结合,发展高光谱图像高性能实时处理技术;要紧密结合应用需求,发挥高光谱遥感的优势和特点,发展新理论和新方法。 相似文献
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高光谱遥感以其波段数目多、光谱分辨率高、带宽窄等特点受到了国内外研究者的广泛关注,它的发展可以说是遥感技术领域的巨大进步。本文主要介绍高光谱遥感的发展,以及针对高光谱影像独有的特点所要进行的数据处理方法。在此基础上,结合青藏高原独特的地理地质环境,探讨高光谱遥感在青藏高原的应用潜力。 相似文献
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针对多光谱和高分辨率全色影像的融合,本文对IHS、HSV、lαβ等几种常见的基于色彩变换的融合方法进行了详细的介绍。通过对融合影像光谱损失的分析,改进了基于IHS变换的融合方法;通过实验对两组影像融合效果进行了全面的分析对比。实验结果表明,该方法在提高融合影像空间分辨率的同时,能更好地保证影像的光谱质量。 相似文献
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主分量变换法对SAR影像同TM影像进行融合 总被引：1，自引：0，他引：1
介绍了采用主分量变换法对SAR影像同TM影像进行融合的方法步骤和算法。此方法不仅能提高多光谱影像的信息量和空间分解力,而且很大程度上保留了原多光谱影像的光谱特征,使融合后的影像在量测和解译能力上都有提高。 相似文献
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基于穷举法的高光谱遥感图像地物识别研究 总被引：1，自引：0，他引：1
介绍了一种基于穷举法的高光谱遥感图像地物识别方法.该方法从所有与研究区有关的可能参考光谱中识别出图像上每个像元的最佳匹配光谱,绘制识别结果图,并由图中信息可对参考光谱进行更换,以求得最佳识别结果.并以云南省中甸普朗斑岩铜矿区外围的高光谱遥感图像为例,得到了该区的地物识别图,经实地检验,证实了该方法的有效性. 相似文献
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以福建平和钟腾铜钼矿区为例,简要介绍了Hyperion高光谱数据处理技术,探讨了基于特征谱带的光谱微分及基于完全波形特征的光谱匹配等遥感矿物识别方法,初步识别出该矿区的绢英岩,并为地质资料、野外踏勘以及岩矿鉴定所证实.旨在交流基于高光谱遥感数据的岩矿信息提取方法技术,对高植被覆盖区的遥感技术应用进行探索. 相似文献
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遥感技术应用于地质中的目的之一是分辫和识别出不同的岩石和矿物等地质体,高光谱分辫率遥感则可通过诊断性光谱特征对岩石或矿物成分及结构进行识别。随着高光谱矿物识别方法的不断发展,使得高光谱遥感技术在地学领域的应用由定性分析到定量识别成为可能,也为今后开展成像光谱遥感数据的广泛应用做好了技术准备。介绍了多种岩矿光谱分析的技术方法,并对不同方法的优、缺点及其应用场合进行分析。最后,总结并提出了下一步的工作方向。 相似文献
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Proof of concept of a novel cloud computing approach for object-based remote sensing data analysis and classification 总被引：1，自引：0，他引：1
R. R. Antunes T. Blaschke D. Tiede E. S. Bias G. A. O. P. Costa P. N. Happ 《地理信息系统科学与遥感》2019,56(4):536-553
Advances in the development of Earth observation data acquisition systems have led to the continuously growing production of remote sensing datasets, for which timely analysis has become a major challenge. In this context, distributed computing technology can provide support for efficiently handling large amounts of data. Moreover, the use of distributed computing techniques, once restricted by the availability of physical computer clusters, is currently widespread due to the increasing offer of cloud computing infrastructure services. In this work, we introduce a cloud computing approach for object-based image analysis and classification of arbitrarily large remote sensing datasets. The approach is an original combination of different distributed methods which enables exploiting machine learning methods in the creation of classification models, through the use of a web-based notebook system. A prototype of the proposed approach was implemented with the methods available in the InterCloud system integrated with the Apache Zeppelin notebook system, for collaborative data analysis and visualization. In this implementation, the Apache Zeppelin system provided the means for using the scikit-learn Python machine learning library in the design of a classification model. In this work we also evaluated the approach with an object-based image land-cover classification of a GeoEye-1 scene, using resources from a commercial cloud computing infrastructure service provided. The obtained results showed the effectiveness of the approach in efficiently handling a large data volume in a scalable way, in terms of the number of allocated computing resources. 相似文献
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HUANGPeizhi Poh－ChinLai 《地球空间信息科学学报》2002,5(2):68-73
The geometric and physical analysis methods are conventional methods for the derivation of skeleton lines in the fields of cartography,digital photogrammetry,and related areas.this paper proposes a stepwise approach that uses the physical analysis method in the first stage and the geometric analysis method in the subsequent stage.The physical analysis method analyses the terrain globally to obtain a rough set of skeleton lines for a terrain surface.The rough skeleton lines help to structure the ordering of feature points by the geometric analysis method. 相似文献
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The geometric and physical analysis methods are conventional methods for the derivation of skeleton lines in the fields of cartography, digital photogrammetry, and related areas. This paper proposes a stepwise approach that uses the physical analysis method in the first stage and the geometric analysis method in the subsequent stage. The physical analysis method analyses the terrain globally to obtain a rough set of skeleton lines for a terrain surface. The rough skeleton lines help to structure the ordering of feature points by the geometric analysis method. 相似文献
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舒宁 《武汉大学学报(信息科学版)》1998,(4)
讨论了影像纹理分析的分维估计原理和具体方法,提出了多波段影像纹理概念和实施方法,介绍了以所述原理进行基于分维估计的单波段和多波段影像纹理分析试验的结果。 相似文献
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From fields to objects: A review of geographic boundary analysis 总被引：12，自引：0，他引：12
Geographic boundary analysis is a relatively new approach unfamiliar to many spatial analysts. It is best viewed as a technique
for defining objects – geographic boundaries – on spatial fields, and for evaluating the statistical significance of characteristics
of those boundary objects. This is accomplished using null spatial models representative of the spatial processes expected
in the absence of boundary-generating phenomena. Close ties to the object-field dialectic eminently suit boundary analysis
to GIS data. The majority of existing spatial methods are field-based in that they describe, estimate, or predict how attributes
(variables defining the field) vary through geographic space. Such methods are appropriate for field representations but not
object representations. As the object-field paradigm gains currency in geographic information science, appropriate techniques
for the statistical analysis of objects are required. The methods reviewed in this paper are a promising foundation. Geographic
boundary analysis is clearly a valuable addition to the spatial statistical toolbox.? This paper presents the philosophy of,
and motivations for geographic boundary analysis. It defines commonly used statistics for quantifying boundaries and their
characteristics, as well as simulation procedures for evaluating their significance. We review applications of these techniques,
with the objective of making this promising approach accessible to the GIS-spatial analysis community. We also describe the
implementation of these methods within geographic boundary analysis software: GEM.
Received: 22 March 1999 / Accepted: 7 September 1999 相似文献
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舒宁 《武汉大学学报(信息科学版)》1997,(4)
针对成像光谱仪影像的专题分析，介绍了沿用常规遥感影像分析方法时的原理和新的算法，提出了影像融合方法的应用，说明了这些方法在学术思想上的归属，并简要介绍了各种方法的实验效果。 相似文献
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The uneven distribution of solar radiation due to topographic relief can significantly change the correlation between reflectance and other features such as biomass in rugged terrain regions. In this article, we use the transfer theory to improve the Minnaert approach. After comparing topographic correction methods for Landsat 8 Operational Land Imager (OLI) and EO-1 Advanced Land Imager (ALI) imagery acquired from the mountainous region in Beijing, China, we used visual inspection, statistical analysis, and correlation analysis to evaluate the algorithms and performance of the proposed Minnaert-E approach. The results indicate that corrections based on non-Lambertian methods have better performance than those based on the Lambertian assumption. The correction performances can be ranked as the Minnaert-E, followed by the Minnaert and the SCS+C corrections, and, finally, the C-HuangWei correction, which performed the worst. We found that the Minnaert-E approach can effectively weaken the influence of terrain relief on pixels and restore the true reflectance of the pixels in the relief area. Further analysis indicates that the Minnaert-E has a better effect on image processing where the slope gradient is restricted to less than 10° or between 30° and 43°. 相似文献
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Geocoding has become a routine task for many research investigations to conduct spatial analysis. However, the output quality of geocoding systems is found to impact the conclusions of subsequent studies that employ this workflow. The published development of geocoding systems has been limited to the same set of interpolation methods and reference data sets for quite some time. We introduce a novel geocoding approach utilizing object detection on remotely sensed imagery based on a deep learning framework to generate rooftop geocoding output. This allows geocoding systems to use and output exact building locations without employing typical geocoding interpolation methods or being completely limited by the availability of reference data sets. The utility of the proposed approach is demonstrated over a sample of 22,481 addresses resulting in significant spatial error reduction and match rates comparable to typical geocoding methods. For different land‐use types, our approach performs better on low‐density residential and commercial addresses than on high‐density residential addresses. With appropriate model setup and training, the proposed approach can be extended to search different object locations and to generate new address and point‐of‐interest reference data sets. 相似文献