With urban and township development and E-Government program promotion in China city remotesensing as base data has developed rapidly. The technique demands in accuracy and effective edge detection and extraction fro...
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ISBN:
(纸本)0819451819
With urban and township development and E-Government program promotion in China city remotesensing as base data has developed rapidly. The technique demands in accuracy and effective edge detection and extraction from higher resolution image become important focal area. In the current popular imageprocessing software packages there are some existing edge detection convolution kernels such as Sobel, Robert, Prewitt, Kirsch, Gauss-Laplace kernels. In general the kernels all work based on algorithm of convolution kernel in spatial territory of the image. However, satellite sensors capture spatial and spectral signatures of surface at same time. Use of both spatial and spectral features to establish a edge detection process is a new notion for achieving more accuracy results. In the paper we introduce a spatial and spectral integrated method which is designed in four stages. The result suggests that four stages process can achieve more cleanly and accuracy edges of city constructions than that results of using other algorithms. The procedure is summarized in figure 1.
remotesensing data, especially the hyperspectral remotesensing data, characterize their great quantities. So how to deal with these data is a focus. Database has solved the problem of storing, searching, updating an...
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ISBN:
(纸本)0819451819
remotesensing data, especially the hyperspectral remotesensing data, characterize their great quantities. So how to deal with these data is a focus. Database has solved the problem of storing, searching, updating and maintaining of the data, but it is not satisfactory in disposing them. In recent years, the technology of data warehouse has great development. It can re-integrate, synthesize and separate the data of database, and use the searching pattern of multiple dimensions to realize data mining(DM). This technology has been widely used in commerce to analyze the inner relationship of the numerous data and makes some remarkable achievements in decision supporting. Data warehouse and Data mining technology have been used in GIS. This article would give a set of complete steps and some general methods in using the DM to analyze the remotesensing data, especially in hyperspectral data. And it tries to do some preliminary exploration in using it to deeply analyze the potential relations among the acquired spectra, images and biology parameters of the experiments and get some anticipated possible results.
Contextual classification methods, which require the extraction of complex spatial information over a range of scales, from fine details in local areas to large features that extend across the image, are necessary in ...
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ISBN:
(纸本)081944667X
Contextual classification methods, which require the extraction of complex spatial information over a range of scales, from fine details in local areas to large features that extend across the image, are necessary in many remotesensingimage classification studies. This work presents a supervised adaptive object recognition model which integrates scale-space filtering techniques for feature extraction within a neural classification procedure based on multilayer perceptron (MLP). The salient aspect of the model is the integration within the back-propagation learning task of the search of the most adequate filter parameters. The experimental evaluation of the method has been conducted coping with object recognition in high-resolution remotesensingimagery. To investigate whether the strategy can be considered an alternative to conventional procedures the results were compared with those obtained by a well known contextual classification scheme.
In this paper, we propose a novel and automated line extraction algorithm in multi-spectral images, which fully utilize the complementary information among multi-spectral images. It consists of three main aspects: Fir...
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ISBN:
(纸本)081944684X
In this paper, we propose a novel and automated line extraction algorithm in multi-spectral images, which fully utilize the complementary information among multi-spectral images. It consists of three main aspects: Firstly, edges are extracted from every spectral image. Then, the edge points from all spectral images are grouped into combined line-support regions according to certain fusion rules. Finally, fits the regions and generates the fused lines. The new algorithm is applied to some real multi-spectral images. The experimental results show that the new algorithm is effective.
In this paper, a novel hierarchical image fusion scheme based on wavelet multi-scale decomposition is presented. The basic idea is to perform a wavelet multi-scale decomposition of each source image first, then the wa...
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ISBN:
(纸本)081944684X
In this paper, a novel hierarchical image fusion scheme based on wavelet multi-scale decomposition is presented. The basic idea is to perform a wavelet multi-scale decomposition of each source image first, then the wavelet coefficients of the fused image is constructed using region-based selection and weighted operators according to different fusion rules, finally the fused image is obtained by taking inverse wavelet transform. Ibis approach has been successfully used in image fusion. In addition, with the use of the parameters such as entropy, cross entropy, mutual information, root mean square error, peak-to-peak signal-to-noise ratio, the performance of the fusion scheme is evaluated and analyzed. The experimental results show that the fusion scheme is effectual.
These fusion methods such as IHS transform, Brovey transform and principal components transform could merged two optical image data of different resolutions - a high spatial resolution panchromatic image and a low spa...
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ISBN:
(纸本)0819451819
These fusion methods such as IHS transform, Brovey transform and principal components transform could merged two optical image data of different resolutions - a high spatial resolution panchromatic image and a low spatial resolution multi-spectral image. But these fusion methods required the spectral range of the high spatial resolution panchromatic image equals or approximates to the spectral range covered with the multi-spectral image. This paper brings forward a new fusion method called FM that could merge two optical image data of different spectral range. This paper proposed its algorithm, firstly to filter on the panchromatic image, then to merge the remotesensing data applying algebra ratio. The fused production is more excellent at spectral preservation.
The proceedings contains 108 papers from the conference on SPIE: Third International Symposium on Multispectral imageprocessing and patternrecognition: Part One. The topics discussed include: theory analysis and exp...
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The proceedings contains 108 papers from the conference on SPIE: Third International Symposium on Multispectral imageprocessing and patternrecognition: Part One. The topics discussed include: theory analysis and experimental study on the amount of information in a color night vision system;restoration of color in a remotesensingimage and its quality evaluation;use of discrete chromatic space to tune the image tone in a color image mosaic;an analytical solution to camera motion using the essential matrix;a new technique creates realistic 3D free-form surfaces photographs and paintings and applications of matching Fourier transform to radar refined imaging.
In this paper, the authors proposed a new theory and method, the phase-separation analysis of remotesensing information field of metallogenetic environment for non-model ore deposit prediction. The theory of nonmodel...
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ISBN:
(纸本)081944684X
In this paper, the authors proposed a new theory and method, the phase-separation analysis of remotesensing information field of metallogenetic environment for non-model ore deposit prediction. The theory of nonmodel ore deposit prediction suggests that the forming of ore deposit result from multiple changes of many geological factors;and in a particularly geological environment, the places where tectonic movement of multi-times piled up together probably produce large or giant type deposits;and the existence of great mineralized body maybe lead to some remarkable differences in composition, in structure, in geophysical field and,in geochemical field from the surrounding geological background, even lead to anomalies of biosphere and atmosphere of the earth. Therefore, on the basis of geology and other data, combining RS with GIS, and through decomposing multivariate information fields, feature extracting and seeking anomaly, it is feasible to establish the natural models of ore source bodies to predict related ore deposits correctly.
Data fusion of SAR (during flood event) and LANDSAT TM (before flood event) has been well known to detect flood disaster, owing to that the all-weather and all-time ability of microwave remotesensing and the abundant...
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ISBN:
(纸本)081944684X
Data fusion of SAR (during flood event) and LANDSAT TM (before flood event) has been well known to detect flood disaster, owing to that the all-weather and all-time ability of microwave remotesensing and the abundant information and good interpretation of TM. In this paper, firstly, an approach named TIN (Triangulated Irregular Network) was used for registration, with better accuracy than other general methods. Secondly, according to statistic analysis including interband correlation and entropy, etc. the selection of the optimal bands of TM was discussed. In order to monitor flood event better and more quickly in future, we analyzed various fusion approaches to see which is optimal and less time-consuming with the data of 98's flood happened to the Yangtze River. As a result, the pseudocolor image of composition of TM5-SAR-TM3 is the best, however, the combinations of TM5-SAR-TM2, TM7-SAR-TM2 and TM7-SAR-TM3 are also alternative and feasible.
Two key important techniques of DTM (Digital Terrain Model) modelling from remotesensingimage pair with high resolution (RSIPHR) are introduced in this paper. First is determining conjugate point pair automatically ...
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ISBN:
(纸本)0819451819
Two key important techniques of DTM (Digital Terrain Model) modelling from remotesensingimage pair with high resolution (RSIPHR) are introduced in this paper. First is determining conjugate point pair automatically by image matching. Because the approximate epipolar image pair of some RSIPHR remains quite large y-parallax after relative registration, 2 D relaxation matching should be used in the DTM Modeling. The procedure includes feature point extraction, approximate value estimation, matching and refining, check and filter. Second is the calculation of the spatial coordinates for the conjugate point pair from matching. For IKONOS and QUICKBIRD images, it can be based on the RPC/RPB (Rational Polynomial Coefficients) parameters. Because the coordinate accuracy, computed by RPC/RPB parameters, is quite lower in many cases, a block adjustment with an affine transform of image coordinates should be completed based on some control points. Then, the affine transform and RPC/RPB parameters should be used in computation. If there are control points more than 4, the new, simple and strict geometric model based on affine transformation could be applied for any RSIPHR. Only 8 affine coefficients and one slantwise angle need to be determined by control points. Then, they can be applied in the computation.
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