最新刊期
卷 ， 期 2 ， 2004
- 摘要：In general, two or more images of a single scene are related by the so-called epipolar geometry. Since the epipolar geometry contains all geometric information that is necessary for establishing correspondence, it is commonly used for the extraction of three-dimensional information in computer vision, photogrammetry and remote sensing. The epipolar geometry means that a point （a） in the image is mapped to the point on the known linear line （epipolar line） or non-linear curve （epipolar curve） in the other image. In case of aerial and perspective imagery, the epipolar geometry is mathematically well founded and widely used in computer vision and aerial photogrammetry. It is told that the epipolar geometry of the linear push-broom sensor is different from that of the perspective one and that the epipolar geometry of perspective imagery cannot be applied to linear push-broom imagery. This paper addresses the epipolar geometry of linear push-broom imagery. Compared with the epipolar geometry of frame perspective images, we qualitatively analyze the epipolarity model of perspective and aerial imagery and propose an epipolarity model of linear push-broom sensor images. The proposed epipolarity model is a non-linear hyperbola curve, based on the approach of track of projection and depends on the sensor model of collinear equation. We discuss the pro- perties of epipolar curves of linear push-broom sensor images, experiment with a kind of classical linear push-broom sensor images: SPOT, draw a conclusion about the epipolar geometry of linear push-broom sensor images, and build the theoretical basis for the application of epipolar curves.关键词：epipolarity;linear CCD push-broom;frame perspective
- 198
- |
- 468
- |
- 10
发布时间：2021-06-10 - 摘要：The mechanism of open complex objects’ thermal radiation characteristics has been elucidated. But in retrieval of LST, the high correlation of multi-angle data is the dominating obstacle for better retrieval. Taking advance of predefined knowledge can improve precision. In this paper, we divided the received radiation brightness to two parts, one is the average brightness of a land area and the other is the relative departure of each pixel to the average. We considered that the former can retrieve the average component temperature by the Matrix Expression directly and the latter can retrieve the component temperature’s relative departure by a statistical matrix. This statistical matrix is a regressive one, which still keep the linear relationship between the measured departure and retrieval departure. We utilized the least-square rule to get the regressive matrix ,which includes the statistic characteristics of retrieved brightness of sensor and the land component radiation brightness. Our simulated experiment also validated this method. We point out that at present the lack of great deal of measured data of matching data from sensor and land limit the generalization of this method.关键词：matrix model;component temperature retrieving
- 121
- |
- 270
- |
- 4
发布时间：2021-06-10 - 摘要：This paper presents an idea to determinate the variant matching relationshinps among areal entities based on the overlay areas. Then a methodology to identify the counterpart elements based on the fuzzy classification of topological relationship is illustrated, which applies the concept of morphologic distance between areas introduced by Winter and the concept of fuzzy topological relationship theory. The resulted topological relationship between areas indicates the discre pancy between the considered areal features and also shows the degree of being or not being belonged to the identical features, which is important for further analysis or decision making. The methodology presented here enhances the technology of feature matching in the area of map conflation. Tests show that the method is well performed and has the ability to identify the non-one-to-one matching relationship and is well suited for areal feature matching among urban geographic databases with the same scales as well as similar scales.
- 141
- |
- 753
- |
- 42
发布时间：2021-06-10 - 摘要：This paper evaluates the image data quality for CBRS-1’s CCD by quantitative method, and provide a group of reference calibration coefficients for its CCD data by cross calibrating method using LANDSAT 7 ETM+ data. The paper obtains the stripe intension information of CCD image by statistical analyzing method, computes the CCD data noise using structure function method, and characterizes the spatial texture of CCD and LANDSAT 7 ETM+ via power spectrum analyzing. The paper calibrates the CCD band 1-4 spectral data, and calculates its dynamic range through corresponding LANDSAT 7 ETM+ data using cross calibration technology. The validation for the cross calibration shows that CCD band 1-3 maximum reflectance error is 1.98% based corresponding LANDSAT 7 ETM+ band,minimum reference error is 0.03%, average value is 1.31%, the maximum error of CCD band 4 is 4.41%, average value is 3.02%. This result indicates that this new cross calibration coefficient is valuable and useful.关键词：CCD data quality;noise analysis;power spectral;cross calibration
- 151
- |
- 814
- |
- 34
发布时间：2021-06-10 - 摘要：Speckle in synthetic aperture radar （SAR） images disturbs SAR images calibration, validation, and interpretation. Thus in most cases of practical interest, reducing speckle in SAR images is a goal towards which we aspire. Over the past 20 years, numerous methods to reduce speckle have been proposed based on digital image processing after the images have been formed. A number of filters have been proposed to reduce speckle based on speckle models, such as the Lee, the Kuan, the Frost, the modified Lee, modified Frost, and filters based on the Maximum A Posteriori （MAP） probability. Meanwhile other filters are not based on speckle models, such as median filter, geometric filter, and wavelet transform filter but also have been applied to reduce speckles. The primary goal of these methods is to reduce speckle without destroying resolution and edge information. In fact, the experiments indicate that there is always a kind of tradeoff between smoothing out speckle and preserving the useful information. It is an inverse problem to restore images with speckle on mathematical physics view. The common attribute of inverse problem is ill-conditioned. Thus, it is impossible to obtain the true image from the images with speckle. Even so, approximate image can be restored from images with speckle on certain condition. In fact, many methods to restore image with speckle have been proposed based on different principle. The different images can be acquired from the same image with speckle using different filters. This makes a problem that which image is optimal. In the general, an optimal filter is well-balanced in the quality of visual appearance, mean preservation, edge preservation, and reduction of the standard deviation. In this paper, an enhanced SAR speckle filter is developed. It can effectively smooth out speckle while preserve edge information.关键词：SAR;speckle;Filter
- 154
- |
- 596
- |
- 14
发布时间：2021-06-10 - 摘要：The simulation of distributed targets is very important to the design of synthetic aperture radar （SAR） systems. Since the end product is SAR images, the echo of SAR signals needs to be simulated and then processed form SAR images, and the parameters needs to be measured and the performance of the images should be, and then evaluated. The designing parameters of SAR could be adjusted to meet the requirement of users before developing SAR systems, specially in space-borne SAR systems. The simulation data is also needed during the developing and debugging of a space-borne SAR real-time processor. Another purpose of simulation is to supply a great deal of simulation images to train image users of space-borne SAR before it launch. Since significant computation is required to simulate a large area distributed targets, it may speed a lot of time, so it is very important to research a more efficient algorithm. A fast algorithm based on FFT is presented in this paper. It reviews the procedure of SAR systems return wave formed. A distributed target can be divided into many more facets, and each facet can be considered as a point targets with specific Radar Cross-Section （RCS） and unlimited small size. Generally speaking, the SAR raw signal is the appropriate superposition of returns from each facet. Noticeable, each return from every facet is the convolution of an impulse with specific amplitude and phase and the transmitting signal of SAR. So we can calculate the superposition of each impulse from each facet first. And then we can get the Fourier Transform （FT） of returns from all facets by multiply the Fourier Transform of impulses and transmitting signal. Finally, the raw returns wave can be generated by taking an Inverse Fourier Transform （IFT）. Since SAR is a discrete and band-limited system, the impulse can be calculated by an interpolation with sinc function kernel in time-domain. And the Fourier Transform can be calculated using fast Fourier Transform （FFT）. Interpolating error depends on the amount of interpolated points and the impulse position between two sampling points. More interpolated points, less error, and impulse position is closed to any of the two sampling points, the error is decreased. The relationship between the error and the two factors is presented in detail in this paper. To improve the precision of interpolations, the amount of interpolated points can be increased. But this method may increase computation linearly. The other method is reducing the interval of sampling points. Based on the second idea, an improved algorithm is introduced. It refer to upsampling and extending spectrum before Interpolating, and a low-pass filter and downsampling after Fourier Transform. This algorithm can improve efficiency and precision as the cost increasing its FFT computation. Finally, the algorithm is implemented in a code whose performance is described and illustrated by a number of examples.关键词：SAR;simulation;return wave;algorithm
- 148
- |
- 604
- |
- 10
发布时间：2021-06-10 - 摘要：It is well-known that, because the object scales in remote sensing images change over wide and unpredictable ranges, a problem in selecting adaptive scale filter is existed for extracting different scale objects in remote sensing images. Aiming at object scales in remote sensing image change uncertain, we introduce one class of Gaussian antisymmetric wavelets based on Gaussian kernel, which extends to Mallat Gaussian wavelet （σ=1）. Coefficients of spatial filter related to the class of Gaussian antisymmetric wavelets given in the paper are derived adaptively by selecting appropriate parameter σ values for special scale object extraction in SAR. Five group coefficients of spatial filter related to the antisymmetric wavelets have been given in this paper. It is important that ones develop interesting operators for the object recognition of SAR images and investigate approaches for feature detection in multi-resource remote sensing images. Because `speckle’ in SAR images is a multiplicative noise, we performed firstly logarithm transform over the two SAR images in preprocessing. Then the features in the logarithm images may be detected in the wavelet transform. It is shown by our experiments in two SAR images that the class of Gaussian antisymmetric wavelets is very efficient for feature extraction in remote sensing images, in which object scales change over wide ranges. Because there exist both step and roof edges in remote sensing images, maximum modulus, or zero-crossings of antisymmetric wavelet transforms can be used for edge feature detection, but the results detected exist local position discrepancy. The conclusion is important to explore new edge detectors in remote sensing images and new technology related to all automatic digital photogrammetry in future.关键词：class of Gaussian antisymmetric wavelets;feature extraction of image;SAR image
- 135
- |
- 309
- |
- 4
发布时间：2021-06-10 - 摘要：The existing method of accuracy determination for image recertification mainly from the accuracy estimation of the control points. However, adding the technology of spatial visualization to the accuracy determination and giving the whole expression for that is the main idea of this paper. So the conformal transformation model for the image rectification is taken as a beginning to deduce the relation between the accuracy of an arbitrary point and the accuracy of control points. And according to such relation, the Inverse Distance Power method is used to give the spatial interpolation for the image rectification accuracy, which also achieved the interpolation value in x or y directions and of the point moving accuracy. Based on above, the visualizations of accuracy is put forward to give the detail description for the quality of image rectification. A case image is also adopted in this paper to give the explanation for spatial visualizations of accuracy, and also some helpful conclusion is obtained for its availability.关键词：spatial interpolation;image rectification;accuracy;spatial visualization
- 161
- |
- 331
- |
- 4
发布时间：2021-06-10 - 摘要：The automatic classification methods for remote sensing images are usually based on statistic information of the images. It has correlation among multi-spectral remote sensing images, and the correlation is a disadvantage to automatic classification of remote images. Commonly, Principal Component Analysis （PCA） is used to remove the correlation. Independent Component Analysis （ICA） can obtain higher order statistics information than PCA. It not only can remove the correlation, and also can obtain band images that are mutual independent. Firstly the fundamental of Independent Component Analysis is briefly introduced. Then, a fast algorithm of ICA （FastICA） and its modification （M-FastICA） are introduced, and are used to classify the remote sensing images. In the result, compare to basic FastICA algorithm, M-FastICA runs quickly and has better convergence performance, and improves the validity of the ICA in classifying of the remote sensing images.关键词：independent component analysis;principal component analysis;fixed-point;remote image;self-adaptive min-distance classification
- 191
- |
- 1049
- |
- 22
发布时间：2021-06-10 - 摘要：MODIS image is a kind of new and important data for global change research. After analyzing in the depth causes of MODIS data distortion, an optimal method to remove the geometric distortion is developed. The longitude and latitude coordinates, obtained by MODIS sensor, are used to remove the distortion of the 1km resolution MODIS data; For 250m and 500m resolution MODIS data, the same resolution coordinates are calculated by the spline interpolation, then the geometric distortion is removed. Because of the spatial irregularity of MODIS 1B data, a method with forward gridding approach and the inverse gridding approach is utilized to allocate a pixel’s position of the geometrically corrected data in the original image. By computing the overlap degree of the current position, the number of the pixels used to calculate the value of the output pixels, the search window sizes and the accurate position of the windows are decided. The value of output pixels is calculated by the distance inverse weight method. All optimal approaches above will improve the processed image’s quality and the processing efficiency. The software based on the above approaches is developed in the Visual C ++6.0 environment. From the result, the conclusion that the approaches are practical and reasonable can be made.关键词：MODIS 1B data;geometric correction;spline interpolation;resampling;software development
- 154
- |
- 1466
- |
- 15
发布时间：2021-06-10 - 摘要：GIS （or Geographical Information System） works well on spatial data manage but has shortage in spatial analysis. Many spatial decision-making problems are dependent on spatial analysis so it is essential to extend the function of GIS analysis. Spatial decision support system has become an important research area in GIS and the traditional methods rely on analysis models while focus little on the importance of knowledge. Model-based decision support system presumes that the real world is structured and can be well simulated. But the fact is that most of the decision problems are ill-structured and cannot do without domain knowledge. How to acquire sufficient decision-related knowledge and well organize it imposes a great challenge both to spatial information science and AI （artificial intelligence）. In this paper, an object-oriented spatial knowledge representation is proposed. The foundation of this method is based on knowledge analysis and knowledge classification. The fact that domain knowledge has layer structure should be considered when knowledge base is designed. The layer structure and organization of domain knowledge class and classification model know are given in this article. The whole knowledge used can be classified into decision area class, decision area sub-class, knowledge class of decision area sub-class, sub-knowledge class and knowledge unit according to the layer structure of knowledge from the top to bottom. Each knowledge class encapsulates attributes, methods and some rules. The detail of spatial reasoning controlled by knowledge unit is illustrated. Based on our method proposed, an application in intelligent spatial decision support system in agriculture is introduced. The function of GIS offers basic spatial data and facts that are the input of spatial decision-making module. In this way GIS and knowledge-based reasoning can be integrated.关键词：GIS;knowledge representation;objectoriented;spatial reasoning;intelligent spatial decision support
- 151
- |
- 560
- |
- 4
发布时间：2021-06-10 - 摘要：The hazard of forest insects and diseases has been worsening in our country and cause great damage each year. A principal factor is that early and mid-term forecasting of could not be done accurately to controll the hazards at the initial stage.Although it’s still far away from predicting accurately the occurrance and development process of forest insects and disease, it’s possible to detect the early hazard spots through the techniques of remote sensing so that the damage can be reduced greatly.A methodology to monitor early spots of forest insects and disease with TM data is discussed in this paper, and it has been proved very efficient.Satellite remote sensing has provided a good instance for macroscopic monitoring and warning of severe forest insects and disease in our country.关键词：pine caterpillar;remote sensing;monitoring
- 180
- |
- 733
- |
- 29
发布时间：2021-06-10 - 摘要：According to the biological basis, basic structure and learning algorithms of Kohonen network, an image classification method is introduced.Pre-processing the image with principal component analysis method based on spectral characteristics of the land use types in the experimental area, and training Kohonen self-organization mapping with geographical ancillary data, land use classifications of Kohonen network are made by integrating image with geographic ancillary data.The classification results are analyzed and compared with the results obtained by Back-Propagation neural network and Maximum Likelihood.The result shows that the classification with geographic ancillary data can improve the image classification accuracy of Kohonen network.关键词：Artificial neural Network;self-organization;land use;RS image classification
- 173
- |
- 758
- |
- 15
发布时间：2021-06-10 - 摘要：The hyperspectral reflectances of the canopy, the leaf on the main stem of two varieties of rice are measured by a ASD FieldSpec Pro FR FM in field and indoor under 3 nitrogen support levels in different stages. The contents of chlorophyll and carotenoid of canopies and leaves corresponding to the spectra were determined. The spectral difference are clear for the canopy and leaves of rice under different nitrogen levels, and the spectral reflectance are gradually getting smaller in the visible region and bigger in the near infrared region along with nitrogen level increasing. The spectral reflectance of the third unfolding leaf from the top on the main stem were bigger than that of the first one from the top in the visible region and the near infrared region at jointing stage and booting stage. There were `red shift’ phenomena before booting and `blue shift’ after heading for the position of red edge λ red, slope of red edge Dλ red and area of red edge S red of the canopy spectra. The leaf area indices（LAI）, above ground fresh biomass（AFM）, above ground dry biomass（ADM） and fresh leaf mass（FLM） were very significantly correlative to the spectral variables R 1200/R 550, R 990/R 550, R 800/R 550, R 750/R 550, λ red and S red. The pigment contents of canopies and leaves were also significantly correlative to the spectral variables R 800/R 550 and λ red. This indicated that some right spectral variables would be used to estimate the LAI, AFM, ADM, FLM and the pigment contents of canopy and leaf for rice.关键词：rice;nitrogen support level;hyperspectral reflectance;spectral variable;red edge parameter
- 182
- |
- 727
- |
- 146
发布时间：2021-06-10
- Postal code：100190
- Tel：010-58887052 Email：nrsb@aircas.ac.cn
- Technical support is provided by Beijing Founder electronics co., LTD 京ICP备20021838号-9
京公网安备11010802024621 - It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
- Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.
0