Many studies have demonstrated that multiple classifier systems, such as the random subspace method (RSM), obtain more outstanding and robust results than a single classifier on extensive patternrecognition issues. I...
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Many studies have demonstrated that multiple classifier systems, such as the random subspace method (RSM), obtain more outstanding and robust results than a single classifier on extensive patternrecognition issues. In this paper, we propose a novel subspace selection mechanism, named the dynamic subspace method (DSM), to improve RSM on automatically determining dimensionality and selecting component dimensions for diverse subspaces. Two importance distributions are proposed to impose on the process of constructing ensemble classifiers. One is the distribution of subspace dimensionality, and the other is the distribution of band weights. Based on the two distributions, DSM becomes an automatic, dynamic, and adaptive ensemble. The real data experimental results show that the proposed DSM obtains sound performances than RSM, and that the classification maps remarkably produce fewer speckles.
The state of Rajasthan is one of the regions of India that has scarce water resources In the desertic terrain of the state there are large numbers of palaeochannels that are considered to be potential aquifers for the...
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The state of Rajasthan is one of the regions of India that has scarce water resources In the desertic terrain of the state there are large numbers of palaeochannels that are considered to be potential aquifers for the region However detection and delineation of these palaeochannels is a challenging task because most of the surface signatures are obliterated by recent alluvial cover or the land use pattern In the present study multi-resolution multi-temporal satellite data products from a suite of satellites such as IRS-1D and Landsat MSS were digitally enhanced and used to detect the palaeochannels One of the prominent palaeochannels delineated was investigated to evaluate aquifer parameters by conducting pumping tests Pumping test data from aquifers surrounding the palaeochannel were also collected and compared in order to assess the relative groundwater prospects of the aquifer An Integrated approach which included interpretation of multi-temporal satellite data slope variation drainage geomorphology and field investigation has helped to detect several palaeochannels in the study area The study also confirms that the palaeochannel aquifer has more potential than the surrounding aquifers (c) 2010 Elsevier B V All rights reserved
In this paper, we use the aspect ratio of a vessel for its recognition and classification with overhead images. For aspect ratio extraction, a morphology-based local adaptive threshold method of detection has been app...
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ISBN:
(纸本)9780819481658
In this paper, we use the aspect ratio of a vessel for its recognition and classification with overhead images. For aspect ratio extraction, a morphology-based local adaptive threshold method of detection has been applied for a more accurate outline. With Radon transforms on the minimum bounding rectangle regions of those extracted outlines, central axis of each vessel can be got. Thus, the aspect ratio of a vessel could be accurately calculated through scanning the boundary contours of every target by lines along and perpendicular to the direction of central axis. If remotesensing information is also considered, such as the height and pitching angle of shooting, the real values of a vessel can also be calculated.
In order to develop a new object-oriented image classification method with fuzzy support vector machines for land cover, an effective fuzzy membership as a function of fuzzy nearness is used for reducing the effect of...
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Soil organic matter (SOM) is an essential and dynamic variable in terrestrial ecosystem. This study used a method for mapping its spatial distribution by remotesensing technique. An image observed by Landsat 5 was us...
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ISBN:
(纸本)9781424455553
Soil organic matter (SOM) is an essential and dynamic variable in terrestrial ecosystem. This study used a method for mapping its spatial distribution by remotesensing technique. An image observed by Landsat 5 was used to estimate the spatial pattern of surface SOM in a town scale. The results showed that the concentration of surface SOM in study Jianshe town had a negative correlation (r =0.51,P2=0.61, P
remotesensingimage classification is an important and complex problem. Conventional remotesensingimage classification methods are mostly based on Bayesian subjective probability theory, but there are many defects ...
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ISBN:
(纸本)9780819483874
remotesensingimage classification is an important and complex problem. Conventional remotesensingimage classification methods are mostly based on Bayesian subjective probability theory, but there are many defects for its uncertainty. This paper firstly introduces evidence theory and decision tree method. Then it emphatically introduces the function of support degree that evidence theory is used on patternrecognition. Combining the D-S evidence theory with the decision tree algorithm, a D- S evidence theory decision tree method is proposed, where the support degree function is the tie. The method is used to classify the classes, such as water, urban land and green land with the exclusive spectral feature parameters as input values, and produce three classification images of support degree. Then proper threshold value is chosen and according image is handled with the method of binarization. Then overlay handling is done with these images according to the type of classifications, finally the initial result is obtained. Then further accuracy assessment will be done. If initial classification accuracy is unfit for the requirement, reclassification for images with support degree of less than threshold is conducted until final classification meets the accuracy requirements. Compared to Bayesian classification, main advantages of this method are that it can perform reclassification and reach a very high accuracy. This method is finally used to classify the land use of Yantai Economic and Technological Development Zone to four classes such as urban land, green land and water, and effectively support the classification.
To find the defects of the apparatus in a substation in the early stage, an infrared temperature monitoring and warning system is established. This system can monitor the electrical equipment automatically the movemen...
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ISBN:
(纸本)9780819483294
To find the defects of the apparatus in a substation in the early stage, an infrared temperature monitoring and warning system is established. This system can monitor the electrical equipment automatically the movement condition. The systemic circulation gathers the transformer substation electrical equipment the infrared imagery, the extraction goal equipment temperature information, and with the history database creation connection, the synthesis distinguishes the equipment failure information. In view of image gathering when because the mechanical drive creates the deviation, proposed one kind of object-oriented division and the image matching adjustment algorithm, first carries on the object division and the configuration definition to the image, then uses based on the phase correlation carries on the matching with the Harris vertex match image matching method to the deviation image. In this paper, a infrared remote-viewing image registration based on phase correlation and feature points matching is presented. Several experiments illustrate that this method has a good performance of reliability and accuracy.
Monitoring water quality using remotesensing technology is current research focus, the main challenge of which is to design an appropriate inversion model of water quality and an effective simulation platform. For th...
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Inspired by the idea of co-training algorithm, in this paper we propose a novel semi-supervised learning algorithm, co-Gaussian Process (co-GP), under a Bayesian framework. image data are characterized in two distinct...
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ISBN:
(纸本)9781424442966
Inspired by the idea of co-training algorithm, in this paper we propose a novel semi-supervised learning algorithm, co-Gaussian Process (co-GP), under a Bayesian framework. image data are characterized in two distinct views, i.e. two disjoint feature sets. A latent function with a GP prior is employed for each view. In learning process of co-GP, knowledge acquired in each view is transferred by probabilistic labels to the other in turns to enhance learning effect. In this manner, proper parameters are estimated in a bootstrap mode and a satisfying performance can be maintained with only small amount of labeled data. The experiments carried out on multitemporal images validate the proposed algorithm.
Ocean primary production (OPP) is an important indicator of ocean ecological system. The spatial and temporal pattern of OPP is helpful for global climate change study. remotesensing has the advantage of dynamic and ...
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