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检索条件"任意字段=Conference on Image Processing and Pattern Recognition in Remote Sensing"

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The research of a binocular sequence imagery aided navigation technique

The research of a binocular sequence imagery aided navigatio...

引用

3rd International Symposium on Multispectral image processing and pattern recognition

作者： Hu, QW Li, QQ Wuhan Univ Sch Remote Sensing & Informat Engn Wuhan 430079 Peoples R China

ISBN: (纸本)0819451819

This paper discusses stereo photogrammetry analytic principle of the binocular sequence images and deduces the formula of the movement parameters estimate model. An aberrance correction model and sensors 3D spatial relationship calibration method is proposed. On this foundation, the common principle, calculation model and implement preceding and methods of the binocular sequence images aided GPS/INS navigation are summarized. A method that used for positioning and orientation by GPS/INS assisted by motion analysis is proposed. Based on case of rapid scatter when GPS is lost, this method used the constraint offered by relative position and attitude from motion analysis to improve precision of position and navigation and constrain the scatter process. The experiment results of the vehicle navigation in GPS blocking case show the high navigation precision with the technique of the binocular sequence images aided GPS/INS navigation. Key Word binocular sequence image, imagery-aided navigation, movement estimate;photogrammetry model.

关键词： binocular sequence image imacrery-aided navigation movement estimate photograrnmetry model

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On the study of BRDF changing feature of winter wheat in different season

On the study of BRDF changing feature of winter wheat in dif...

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3rd International Symposium on Multispectral image processing and pattern recognition

作者： Zhao, F Wang, J Tang, SH Yan, GJ Jiao, ZT Li, XW Beijing Normal Univ Dept Geog Res Ctr Remote Sensing Beijing 100875 Peoples R China

ISBN: (纸本)0819451819

The anisotropic reflectance of vegetation canopy is mainly determined by its spectral and structural features, and can be described by Bidirectional Reflectance Distribution Function (BRDF). In this article, we select the winter wheat from the beginning of April to the beginning of May 2001 at Shunyi county, north of Beijing, as the research object, to study its BRDF changing rule with the changing time. In the process we compute the structural scattering index (SSI) by inverting the semiempirical linear kernel-driven BRDF model, and analyze its relation with the leaf area index (LAI) of winter wheat. The results show that there is a clear linear relationship between SSI and LAI of winter wheat. So SSI can well be used to reflect the seasonal BRDF changing rule of winter wheat.

关键词： BRDF winter wheat kernel-driven model structural scattering index leaf area index

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Automatic road extraction based snake and line photogrammetry

Automatic road extraction based snake and line photogrammetr...

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3rd International Symposium on Multispectral image processing and pattern recognition

作者： Zhang, ZX Zhang, HW Zhang, JQ Wuhan Univ Coll Remote Sensing & Informat Engn Wuhan 430079 Peoples R China

ISBN: (纸本)0819451819

In this paper, an approach for the automatic extraction of liner feature, in particular roads, from digital aerial imagery is proposed. In some literature, knowledge based automatic road extraction were done with geo-referenced imagery which can automatically register old road map to new imagery as knowledge, Whereas the automatic geo-reference and road extraction are processed simultaneously in this approach, which can benefit and depend on each other. The implemented approach is based on Snake model and template matching with the new aerial imagery and old road map. The presented procedure does not need much manual interaction and therefore has the potential to be integrated into an automatic workflow. Potential applications of the approach are manifold, like automatic change detection of road and three-dimensional reconstruct of man-made objects such as road and building with some minor modifications.

关键词： road extraction active contour models (snake) line photogrammetry template matching

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Road extraction from remote sensing image using support vector machine

Road extraction from remote sensing image using support vect...

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3rd International Symposium on Multispectral image processing and pattern recognition

作者： Mei, TC Li, FP Qin, QQ Li, DR Wuhan Univ Sch Elect Informat Wuhan 430079 Peoples R China

ISBN: (纸本)0819451819

In this paper, we propose a technique that combined template matching and support vector machine for road identification from high-resolution aerial image. It is a model-driven approach that combines both the local and global criteria about the radiometry and geometry of linear structures interested. In this approach, the road center point is extracted by utilizing the general road model. Then the road center point is used as initial point for the template matching through which the road segment is obtained. The road characteristic is learned through the support vector machine that is based on the statistical learning theory. The support vector machine is a powerful learning method that it can get high classification accuracy without too much training sample. These properties can be applied for extracting the road characteristics from few road samples. The support vector machine is used to extract the true road segment and remove the false road segment. The proposed approach has been experimented on high-resolution aerial image and its performance is satisfied.

关键词： template matching feature extraction road extraction support vector machine

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The short wave observation using the optical instrument for detecting microstructure of sea surface wave

The short wave observation using the optical instrument for ...

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conference on Ocean remote sensing and Applications

作者： Wang, YF Guan, S Ding, YY Fu, J Huang, WM State Ocean Adm Inst Oceanog 1 Qingdao 266061 Peoples R China

ISBN: (纸本)0819446785

The marine microwave remote sensing is based on the interaction between the EM wave and the small-scale wave with a wavelength comparable to that of the EM wave, so the most important in-situ work must be done to measure the structure of small-scale wave. The optical instrument for detecting microstructure of sea surface wave is used to obtain the pattern of fine scale wave, and a series of algorithm is developed to calculate the high frequency wave spectrum from the image data. The color-encoding method is used to measure the 2-D structure of water surface. The apparatus consists of 4 parts: the light source, a color-encoding plate, the Fresnel Lens, and 3CCD camera. The color-encoding plate is designed on the basis of the HSI Encoding method. The actual image size measured by the instrument is about 0.4 x 0.3m. The image's sampling rate is 20Hz;the spatial resolution is 1mm with a dynamic slope range of +/-45degrees. The system was successfully deployed in the water tank. The image processing is discussed to introduce how to get the wave number spectrum can be got from the original color slope image. The algorithm will provide a good opportunity for us to solve some problems in marine remote-sensing mechanism and oceanic dynamics.

关键词： surface wave microstructure image processing marine microwave remote sensing

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Structure-Context Based Fuzzy Neural Network Approach for Automatic Target Detection

Structure-Context Based Fuzzy Neural Network Approach for Au...

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2003 IGARSS: Learning From Earth's Shapes and Colours

作者： Jishuang, Qu Chao, Wang Zhengzhi, Wang Key Lab of Remote Sensing Info. Inst. of Remote Sensing Applications CAS Beijing 100101 China Inst. of Mechatronics Eng./Automat. National Univ. of Defense Technology Changsha HuNan 410073 China

This paper proposes a structure-context based fuzzy neural network (SCBFNN) approach for automatic target detection. Fuzzy neural network methods not only possess advantages as adaptivity, parallelism, robustness, ruggedness, optimality, but integrate advantages as depicting and solving system uncertainty by fuzzy set theory, accordingly, they are powerful tools for image processing and pattern recognition. Use fuzziness measures as objective function of neural network can depict uncertainty of pixels' category validly so as to optimize image classification by minimize the objective function. Put information constraint of structure context on neurons' weighting processing can reduce loss of image information, especially, the rich information comprised by target edges, by which target's attributes such as profile and shape can be retained validly, and the false detection rate can also be improved prominently. Experiments on remote sensed images of target are executed to validate SCBFNN approach, and the results exhibit that SCBFNN possesses good ability to automatic target detection, simultaneously, possesses valid abilities to eliminating uncertainty and retaining target shape compared with conventional neural network methods. At last a brief conclusion is given.

关键词： Neural networks

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The region growth algorithm based cosine backscatter model for radarclinometry

The region growth algorithm based cosine backscatter model f...

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3rd International Symposium on Multispectral image processing and pattern recognition

作者： Qian, J Shu, N Zhang, ZQ Wuhan Univ Sch Remote Sensing Informat Engn Wuhan 430072 Peoples R China

ISBN: (纸本)0819451819

In this paper, we set forth the principle of Cosine Backscatter Model. In the model, and a new algorithm that doesn't omit azimuth angle and can extract DEM in mountainous area was introduced. First, the Radar image is divided into several regions by edge information using Laplace algorithm. In one region, the image gray level changes slowly Second, in the same region, we could assume that slope changes slowly, azimuth angle and range angle are affected by their neighbor pixels, the image gray level of pixel is changed by its neighbor pixels. azimuth angle and range angle were assessed from a seed. From known point, we get azimuth angle and range angle respectively by derivative;balance the value through iterative computation by ratio data mid Cosine Backscatter Model. In neighbor regions, we get seed of gradient angle by average gray level of two regions, and give amend index. From this point, we can get other point gradient angle same as the second step. Then we extract DEM in all regions. By applying this model, the DEM of Zhangbei of Hebei province were assessed Through checking against the topographic map, the DEM error is little.

关键词： radarclinometry region growth Cosine Backscatter Model

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Detection and counting of cars in aerial images

Detection and counting of cars in aerial images

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IEEE International conference on image processing

作者： Hinz, S Tech Univ Munich Chair Photogrammetry & Remote Sensing D-80290 Munich Germany

ISBN: (纸本)0780377508

This paper introduces a new approach to automatic car detection in monocular large scale aerial images. The extraction is based on a hierarchical 3D-model that describes the prominent geometric features of cars on different levels of detail. Furthermore, vehicle color, windshield color, and intensity of a car's shadow area are included as radiometric features. The model automatically adapts the expected saliency of different features depending on vehicle color and the current illumination direction which are measured from the image during extraction or given a priori, respectively. Car extraction is carried out by matching the model ,,top-down" to the image and evaluating the support found in the image. In contrast to most of the related work, our approach does not rely on external information like digital maps or site models. Various examples illustrate the applicability of this approach. However, they also show the deficiencies which clearly define the next steps of our future work.

关键词： Object recognition

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An algorithm for identification based on spectral diagnostic feature matching technology

An algorithm for identification based on spectral diagnostic...

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3rd International Symposium on Multispectral image processing and pattern recognition

作者： Chen, ZC Geng, XR Zhang, B Tong, QX Zheng, LF Chinese Acad Sci Inst Remote Sensing Applicat Beijing 100101 Peoples R China

ISBN: (纸本)0819451819

Imaging spectrometers acquire images in a large number, narrow, contiguous spectral bands to enable the extraction of reflectance spectra at a pixel scale that can be used for identification. Many identification methods based on the spectra match technique have been developed. Such as spectral angle mapping, binary encoding. But these methods use all the data in the spectral dimension and compare the whole similarity between the reference and test spectrum. Sometimes two different kinds of spectrums may have big similarity, and this results in the wrong identification. There are also many algorithms using, waveform characters for identification. However these methods maybe ineffective when the spectra have no diagnostic absorption feature. This paper introduces a new algorithm for identification based on diagnostic feature matching technique. Spectral matching technique and waveform characterization are combined for identification. In stead of matching, test spectrum in all the wavelength range, this new algorithm emphasizes diagnostic features' location and only matches several diagnostic features in their most possible locations. To insure the identification accuracy, spectral characters in terms of slope and asymmetry are used to check and verify. The algorithm is processed in four steps which will be described in the second part of this paper. In the third part, this algorithm is tested by identifying Alunite from AVIRIS image in Cuprite, Colorado. The result proved this new algorithm effective.

关键词： hyperspectral image identification spectra matching diagnostic features characterization

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The classification of MODIS images based on band combination

The classification of MODIS images based on band combination

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Third International Symposium on Multispectral image processing and pattern recognition

作者： Li, Yan Zhai, Ruifang Wang, Ying School of Geodesy and Geomatics Wuhan University 129 Luoyu Road Wuhan 430079 China Sch. of Remote Sensing/Info. Eng. Wuhan University 129 Luoyu Road Wuhan 430079 China

This paper discusses the existing three optimal band combination rules of hyperspectral remote sensing images. They are joint entropy, optimal index factor and Sheffield index respectively. Three bands of MODIS images data are combined arbitrarily according to the three rules, so the best three bands combination images of the three rules are acquired. On the basis of this, the three images are all classified in term of maximum likelihood classifier. Also, the influence of each band combination to the classification performance is discussed. The experiment result proves that the best classification performance of the MODIS images based on the three bands combination is the combination image based on optimal index factor.

关键词： image analysis

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