Acta Geodaetica et Cartographica Sinica

GeoGlobe--Geo-spatial Information Sharing Platform as Open Virtual Earth

2010, 39(6): 551-553.

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How to manage the PB level global covered multi-scales mass geo-information, construct the 3D virtual globe, efficient transportation and real-time visualization and specialty GIS integration is the great challenge of the geo-information techniques in our country. Therefore, this paper focus in the theory, method and key techniques of management, network transportation, sharing integration and visualization of the multi-source, multi-scale and multi-date mass geo-information in online three dimension virtual globe. As the basis for it, the open-type of virtual globe sharing integration platform—GeoGlobe is developed, and successfully implicated in a serious item such as National geographic information of public service platform.

Ortho-rectification of Satellite-borne SAR Image Based on Image Simulation

2010, 39(6): 554-560.

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SAR image ortho-rectification in the areas where it is difficult to select points, such as hilly and mountainous terrain, often adopts the method based on the image simulation. The traditional method used the RD model to do the simulation but it needed to establish different modules to do the simulation and ortho-rectification for differents SAR images. This paper proposed the method using the RPC model substituting the RD model to simulate the SAR image in order to address the problem and did the ortho-rectification with the simulated image. Also, this paper improved the method of obtaining gray information from the simulated SAR image. TerraSAR-X images acquired over Sichuan were used as test data. Through the comparision between the actual accuracy and the theoretical accuracy of the ortho-rectification image, the theory and method proposed in this paper were verified.

Estimation of Spaceborne Dual-antenna InSAR Baseline Based on Kalman Filter

2010, 39(6): 561-565.

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High precision measurement and determination of spaceborne InSAR baseline is a key technology in the acquirement of digital elevation information, optical camera and laser range finder were adopted for dual-antenna InSAR system. However, due to the effect of geometry error and instrument error, Kalman filter was designed based on the baseline measurement system and the modal analysis of antenna mast in order to meet the reqiurement of the high precision of interferometric baseline. Simulations conducted show that the vector of interferometric baseline could be precisely estimated by the Kalman filter.

Pixel-level Remote Sensing Images Fusion Based on Heat Conduction Model

2010, 39(6): 566-571.

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A novel pixel-level remote sensing image fusion based on heat conduction equation is proposed in this paper. The main contributions of the paper are as follows: 1) the diffusion relationship between the high-resolution image and the low-resolution image are obtained in the space domain, where Brovey transform (BT) is one of its special cases; 2) a unified expression of pixel-level image fusion and image enhancement is obtained. And a brightness balanced-based image fusion is obtained by using the expression; 3) the disadvantage that the standard variance-based image fusion method will result in the loss of high spatial resolution panchromatic image information for smaller variance low-resolution multispectral images is pointed out. Experimental results show that our approach does not lose the image spatial resolution and spectral information and outperforms the existing method.

Research on Relevance Vector Machine Hyperspectral Imagery Classification

2010, 39(6): 572-578.

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Though the support vector machine has been successfully applied in hyperspectral imagery classification, it has also several limitations. Relevance vector machine is a sparse model in the Bayesian framework, its mathematics model doesn’t have regularization coefficient and its kernel functions don’t need to satisfy Mercer's condition. RVM presents the good generalization performance, and its predictions are probabilistic. In this paper, we firstly analysis the disadvantages of the support vector machine for hyperspectral imagery classification, and then a hyperspectral imagery classification method based on the relevance machine is brought forward. We introduce the sparse Bayesian classification model, regard the RVM learning as the maximization of marginal likelihood, and select the fast sequential sparse Bayesian learning algorithm. Through the experiments of OMIS and AVIRIS images, the advantages of the relevance machine used in hyperspectral remote sensing image classification are given out.

Imaging Model and Image Recovering Algorithms of Spaceborne Camera

2010, 39(6): 579-584.

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A Generic Model of Time-Delay and Integration Charge-Coupled Device (TDI CCD) Push-broom Imaging (GMPI) based on energy was established, through researching the Image Motion Mismatch (IMM) of the space camera in the end of orbit life. For the image motion mismatch being inevitable in the end of orbit life, an Unconventional Way of Remote Sensing Imaging (UWRSI) was proposed based on GMPI, in order to Simplify the calculation, the GMPI was Simplified to a Filter Model of TDI CCD Push-broom Imaging (FMPI), using the Filter Model, the Image-Aliasing Effect (IAE) of the space camera in end of orbit life was Quantitative Analysis easily, and the algorithm and its parameters of image recovering was given out based on imaging parameters. The Original image with IMM were obtained from imaging system with IMM, which was tried to recover to the virtue images using the image recover algorithm, the result showed that the image recover algorithm was effective.

An Uneven Illumination Correction method Based on Variational Retinex for Remote Sensing Image

2010, 39(6): 585-591.

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In the remote sensing imaging instant, the uneven atmosphere and illumination often cause inhomogeneous luminance distribution in the images. This nonuniform phenomenon will affect the further applications of these images. In this paper, a new uneven illumination correction method for optical remote sensing image is presented. The method is based on the Retinex theory and the variational function is used to estimate the uneven illumination distribution in the imaging instant. Retinex theory addresses the problem of separating the illumination from the reflectance in a given image, which in general is an ill-posed problem. The color sensation for any area in an image is not dependent on illumination but on reflectance which should be retained. In the variational Retinex framework, the projected normal steepest descent optimization method is applied to solve the function and the multi-resolution numerical solution is introduced to improve the algorithm efficiency. The proposed algorithm was tested on a synthetic image and two real aerial images. Experimental results validated that the proposed algorithm outperforms the traditional methods in terms of the calculation efficiency, the quantitative measurements and visual evaluation.

Automatic matching of high resolution satellite images base on RFM

2010, 39(6): 592-598.

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Abstract: A matching method for high resolution satellite images based on RFM is presented. Firstly the RFM parameters are used to predict the initial parallax of corresponding points. Secondly the approximate epipolar equation is constructed based on projection tracking and its accuracy is analyzed. Thirdly approximate 1D image matching is executed on pyramid images and least square matching on base images. At last RANSAC is imbedded to eliminate mis-matching points and matching results are obtained. Test results verified the method robust and with high matching rate, compared to 2D gray correlation method and SIFT matching method, and solved the question of high resolution satellite image matching with different time and large rotation images.

Multi-source Remote Sensing Image Matching Based on Contourlet-domain Hausdorff Distance and Particle Swarm Optimization

2010, 39(6): 599-604.

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To further improve the accuracy and efficiency of multi-source remote sensing image matching, an algorithm based on contourlet transform, Hausdorff distance and improved particle swarm optimization was proposed in this paper. Firstly, the target image and reference image were decomposed to the low resolution image using contourlet transform. Then, wavelet modulus maxima algorithm was employed to extract the edges of the low-frequency subbands, and Least-trimmed-squares Hausdorff Distance(LTS-HD) was used as similarity measure for image matching. Meanwhile, the extremum disturbed and simple particle swarm optimization was introduced to get the rough matching results. The position of rough matching results were corresponded to the original image and then the matching between the higher resolution images could be implemented stepwise up to the full resolution images. The experimental results show that, compared with those of other existing sensing image matching methods, the proposed algorithm has the high accuracy, efficiency and strong robustness.

The Algorithm of Image Feature Detection from Phase Congruency Model based on 2-D Hilbert Transform

2010, 39(6): 605-610.

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The algorithm of phase congruency developed from phase information of image in frequency domain, is employed for image feature detection. The theory of phase congruency is that image features, such as step edge, roof, mach band and delta, always occur at points where the phases of harmonic components come to the maximum congruency. This algorithm is realized to extract the image features by constructing the local energy model being normalized to get the value of phase congruency of every point in image. This paper introduces the 2-D Hilbert transform instead of 1-D Hilbert transform to propose the algorithm of phase congruency for detecting the image features. The modified algorithm can take account of the full directions of the image features. Meanwhile, the implementation of phase congruency proposed by Morrone is complex and low effective to calculate phase congruency of each point in image separately, while the proposed method simplifies the calculation of the numerator of local energy by convoluting the original image with the window operator to remove DC (Direct Current) component of current window and 2-D Hilbert transform respectively. Moreover, this algorithm makes the denominator of the model of phase congruency adding the DC component to suppress the noise of image. The modified algorithm of phase congruency is implemented into the natural image and remotely sensed imagery, and the results show that the modified algorithm is effective to detect image features.

A Method of small Water Information Automatic Extraction from TM Remote Sensing Images

2010, 39(6): 611-617.

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Small water body extraction of hilly area from TM images is an important and difficult task. For the large differences in the characteristics of brightness value of water body and shadow in blue-green bands and typical model of multi-band spectal relationship, this paper build a new water information ertraction model of multi-band spectal relationship on the basis of the difference operation. Firstly, water bodies are extracted from shadow and other surface features. Secondly, to connect short-terms and fill empty based on mathematical morphology filtering algorithm. Finally, adoption of binary image thinning algorithm, objective water bodies are refined. After experimental analysis and comparison show that the method overcomes the shortcoming of lot of water extraction methods wihich can only effectively extract larger water bodies. The means not only can automaticly and high-precision extract small water of hills and mountains area, but also can effectively remove the shadows and other interference information.

Urban Building Extraction from VHR Multi-spectral Images Using Object-based Classification

2010, 39(6): 618-623.

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Building extraction in urban environment requires high spatial resolution remotely sensed data. However, traditional pixel-based classifiers based on spectral features are ineffective for high-resolution multi-spectral images due to large within-class spectral variations and between-class spectral confusions. In this study, a rule-based object-oriented classification method for building extraction is developed from an Ikonos urban scene. The method includes the following steps: (1) fusion of 1m panchromatic and 4m multispectral bands to produce a pan-sharpened 1m multispectral image; (2) segmentation of the 1m dataset; (3) supervised object-based classification into broad spectral classes; and (4) spectral, spatial, textural and contextual parameters developed from sample building objects are implemented in a fuzzy logic rule base to separate building rooftops from other impervious surface classes. The rule-based method identifies building rooftops with 93% accuracy in the experiment.

Digital Close-range Stereo Image Matching Based on Digital Parallax Model and Improved SIFT Feature

2010, 39(6): 624-630.

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For the purpose of automatic and effective stereo image matching in the field of digital close-range stereo photogrammetry, a new stereo image matching algorithm based on Digital Parallax Model (DPM) and improved SIFT feature is proposed in this paper. In the new algorithm, considering characteristics that baseline and relation of two cameras is fixed in digital close-range photogrammetry system, digital parallax model of stereo image is constructed firstly, and computation parameters for confirming conjugate epipolar line are work out with known calibration data. Then searching scope of conjugate points on the right image is confirmed under constraints of DPM and epipolar line to improve matching speed and accuracy. Secondly, to increase matching robustness, the computation model of matching similarity measure combined with local structure information and global gray-value information is designed by SIFT feature and gray-value feature. The new algorithm is applied to actual stereo images taken by digital close-range photogrammetric system. Experimental results show that the proposed algorithm can decrease matching error greatly, and enhance the reliability and precision of stereo image matching.

The calibration of the scan line camera based on laser scanner

2010, 39(6): 631-635.

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Based on the characters of the line scan camera and the vehicle-borne 3D data acquisition system, it presented a method which is for the calibration of the scan line camera (SLC) based on the laser scanner. The SLC has many advantages, such as high frequency and wide view angle, which is better than a frame digital camera in saving images and getting a complete image. But it also has a same problem: lens distortion. SLC and LS are two important parts of the the vehicle-borne 3D data acquisition system. It uses SLC to grab the color texture information of the objects, and uses the LS to get the 3D coordinate information of the objects. The two sensors have a common character: during the acquisition the LS data is a line which is made up with discrete points and the SLC data is a color line. Base on this character it presented a method which is for the calibration of the scan line camera (SLC) based on the laser scanner. Using the angle information from the original laser scanner data, combing the principle of the scan line camera, it built a calibration model for SLC and designed some experiment method for that. Then it computed high precision calibration parameters, which provides basis for the texture mapping in the future and gives references for the similar sensors calibration.

Application of Parallel Computing with OpenMP in Data Processing for Satellite Gravity

2010, 39(6): 636-641.

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The computation-intensive tasks in the data processing for satellite gravity are analyzed in this paper and some key tasks which need to be parallelized for the performance improvement are summarized. By the comparison between the parallelization methods, the OpenMP is adopted and the validity of the parallelization is demonstrated by some examples. The results show that the parallel computing can improve the efficiency of data processing of the GRACE/GOCE mission remarkably.

Disposal of Spatial Conflict Between Roads and Buildings based on the multilevel displacement principles

2010, 39(6): 649-654.

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By analyzing the advantages of traditional algorithm of disposing the spatial conflict between roads and buildings, one new method is brought forward, which refers to simulating the method of manual displacement and keeping the general spatial layout of the buildings well. Firstly, the multilevel spatial disposal principles between the roads and buildings of different regions are put forward in terms of the difference of region density. The multilevel spatial disposal principles refer to three levels: one is to keep the origin distance scale, spatial relation and spatial layout in the sparse region, the other is to keep the minimal distance and spatial orientation relation in the dense region, the third is to only keep the minimal distance in the high-dense region. Then, the displacement layers of buildings are built according to the neighbor degree between buildings and roads. And the displacement operation will be executed respectively according as fore-and-aft displacement layer order. When disposing the conflict and displacing the buildings, the multilevel spatial disposal principles spread through the calculation and aggregation of extern forces and the design of displacement algorithm on the buildings. The spatial conflicts between the road and building, and the conflicts between the buildings, are disposed especially.

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