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Multi-scale semantic model for unsupervised object segmentation

2012 2nd International Conference on Materials Science and information technology, MSIT 2012

作者： Li, Yu Li, Xiangjuan Zhang, Yasen Sun, Xian Wang, Hongqi Institute of Electronics Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9783037854389

It is difficult to segment instances of object classes accurately unsupervised in images, because of the complexity of structures, inter-class differences, background interference and so on. A multi-scale semantic model method is proposed to overcome the disadvantages existing in most of the relative methods. This method uses generative model to deal with the objects obtained by multi-scale segmentations instead of whole image, and calculates kinds of visual features to mine the topic information of every object. In the segmentation process, a semantic correlative function of every segment block based on KL divergence is built up and minimized to select the object correct regions. Experimental results demonstrate the effectiveness of the proposed method. © (2012) Trans Tech Publications, Switzerland.

关键词： Semantics

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Multi-objects detection in remote sensing images using multiple kernel learning

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2012 2nd International Conference on Materials Science and information technology, MSIT 2012

作者： Li, Xiangjuan Sun, Hao Zheng, Xinwei Sun, Xian Wang, Hongqi Institute of Electronics Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9783037854389

The objective of this work is multiple objects detection in remote sensing images. Many classifiers have been proposed to detect military objects. In this paper, we demonstrate that linear combination of kernels can get a better classification precision than product of kernels. Starting with base kernels, we obtain different weights for each class through learning. Experiment on Caltech-101 dataset shows the learnt kernels yields superior classification results compared with single-kernel SVM. While such a powerful classifier act as a sliding-window detector to search planes in images collected from Google Earth, results shows the effectiveness of using MKL detector to locate military objects in remote sensing images. © (2012) Trans Tech Publications, Switzerland.

关键词： Object detection

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A new ship detection method for massive data high-resolution remote sensing images

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2012 2nd International Conference on Materials Science and information technology, MSIT 2012

作者： Sun, Hao Li, Yu Liu, Ge Long, Hui Wang, Hongqi Institute of Electronics Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9783037854389

This paper proposes a new method for automatic ship targets detection in remote sensing images. The method uses adaptive segmentation algorithm for getting possible ship targets first, and then calculates Histograms of Oriented Gradient (HOG) feature to extract the structural information of ships, followed by supervised learning algorithm to identify the possible ship targets. Multi-scale sliding-window is used to handle targets with different scales. The experimental results prove that this new method has a good precision and robustness for most of the ship targets and give attention to the efficiency.© (2012) Trans Tech Publications, Switzerland.

关键词： Ships

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A method for object occlusion handling based on multilevel track queues

A method for object occlusion handling based on multilevel t...

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International Conference on Multimedia and Signal processing

作者： Jin, Biao Hu, Wenlong Zhang, Yu CAS Graduate School Key Laboratory of Technology In Geo-spatial Information Processing and Application System Institute of Electronic Beijing China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronic Chinese Academy of Sciences CAS Beijing China China Electric Power Research Institute Beijing China

ISBN: (纸本)9780769543567

Multi-object tracking is important in many computer vision applications. The major difficulties are due to inter-object or scene occlusion and data association. In this paper, we present a method to automatically detect and track multiple objects in complicated scenario from a single camera that is stationary. The proposed detecting method can prevent the moving objects updated to the background and can restrain ghosts. The moving objects are modeled fusing the hue and edge features. The system achieves tracking the object using the proposed associated strategy based on multilevel track queues. Experiments show the effectiveness of our approach under different conditions with complete occlusions. © 2011 IEEE.

关键词： Object detection

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Unambiguous parameter estimation of radial velocity approach for airborne SAR-GMTI

Unambiguous parameter estimation of radial velocity approach...

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2011 3rd International Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2011

作者： Xu, Ruipeng Zhang, Dandan Huang, Lijia Hu, Donghui Ding, Chibiao Key Laboratory of Geo-spatial Information Processing and Application System Technology Institute of Electronics Chinese Academy of Sciences Beijing China

ISBN: (纸本)9788993246179

The ambiguous Doppler centroid causes incorrect estimation result of the radial velocity. For moving targets with fast radial velocity, an unambiguous estimation approach of the radial velocity is introduced for the airborne SAR system in this paper. First, two channels carried different wavelength can be constructed by range multilook processing (RMLP). Second, the instantaneous frequency curve of the moving target is obtained by polynomial fitting for each channel, where the linear term denotes the baseband Doppler centroid. Considering the fact that the difference of the estimated baseband Doppler centroid in two channels is equal to the difference of the absolute Doppler centroid, the unambiguous radial velocity can be estimated using it. Third, the range walk and the Doppler shift which are produced by the fast radial velocity can be eliminated by compensating a phase in the range-frequency and azimuth-time domain. As a result, the moving target will be reimaged and relocated after azimuth compression. The proposed approach will be applied to both single- and multi-channel SAR system. The simulation results validate the effectiveness of the proposed method. © 2011 KIEES.

关键词： Parameter estimation

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Improving wetland mapping by using multi-source data sets

Improving wetland mapping by using multi-source data sets

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2011 International Symposium on Image and Data Fusion, ISIDF 2011

作者： Ji, Luyan Jiang, Kang Geng, Xiurui Tang, Hairong Yu, Kai Zhao, Yongchao Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Science Beijing China

ISBN: (纸本)9781457709692

To conserve and manage wetland resources, it is important to map wetlands and monitor their changes. However, wetland mapping is difficult because of spectral confusion with other landcover classes and spectral variability among different types of wetlands. This paper demonstrated a multi-source based approach for improving the accuracy of wetland mapping. According to the formation of wetland, variables derived from multi-source image date, and other ancillary GIS layers were first integrated to create the possible region for wetland (PRW). And then classification was conducted within the PRW to map wetlands. PRW could greatly reduce the amount of other land cover classes that participated in the classification, therefore reducing both the difficulty of wetland mapping and the commission error rate. In this study, we chose the test area in Dongzhai Harbor, Hainan Island, China, where the main wetland type is mangrove. The mapping was based on LANDSAT TM/ETM+ imagery combined with DEM data, and the ancillary GIS data included available water, soil and vegetation layers. The thematic accuracy of the mapping was assessed using highresolution images from Google Earth and local wetlands databases. Classification of the 2001 Landsat ETM+ scene alone resulted in consumer's accuracy of 65% and Kappa coefficients of 0.69, whereas the multi-source based approach with the same training samples resulted in an accuracy of 86% and 0.80. The developed method is portable, relatively easy to implement, and should be applicable in other landcover classes and over larger extents. © 2011 IEEE.

关键词： Wetlands

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An invariant generalized Hough transform based method of inshore ships detection

An invariant generalized Hough transform based method of ins...

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2011 International Symposium on Image and Data Fusion, ISIDF 2011

作者： Xu, Jian Fu, Kun Sun, Xian Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781457709692

Automatic inshore ship detection from remote sensing imagery has many important applications, such as ship change detection and harbor dynamic surveillance. Stable performance of inshore ship detection is vital to the analysis of ship change and then determines the harbor surveillance effect. However, it is hard to detect inshore ships utilizing the traditional area-based method because the grayscale and texture character of inshore ships are similar to that of the shore. In this paper, a new method based on invariant generalized Hough transform is introduced to extract ship shape using the evidence-gathering procedure. In contrast with other shape extraction methods used in inshore ships detection, our method is specially tolerant to noise and occlusion, and also invariant to translation, scale and rotation transformation. Moreover, our method can be used to separate ships moored together that can benefit to ship recognition. Experiment results are demonstrated on the optical remote sensing imagery from Google Earth. © 2011 IEEE.

关键词： Ships

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Improved calibration method of the airborne polarimetric SAR

Improved calibration method of the airborne polarimetric SAR

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2011 3rd International Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2011

作者： Ming, Feng Hong, Jun Zhang, Lintao Institute of Electronics Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Geo-spatial Information Processing and Application System Technology CAS Beijing 100190 China National Key Laboratory of Microwave Imaging Technology Beijing 100190 China Graduate University of the Chinese Academy of Sciences Beijing 100039 China

ISBN: (纸本)9788993246179

The PolSAR system must be calibrated before obtain effective polarimetric information. The airplane attitude is unstable during the PolSAR measurement, which will impact the polarimetric calibration precision. This paper improved the polarimetric calibration method proposed by Whitt considering the impact of airplane attitude. The improved method is proved by polarimetric experiment using a PolSAR system developed by IEcas(Institute of electronics, Chinese Academy of Sciences). © 2011 KIEES.

关键词： Calibration

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A new fusion algorithm for optical remote sensing data

A new fusion algorithm for optical remote sensing data

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2011 International Symposium on Image and Data Fusion, ISIDF 2011

作者： Yu, Kai Hu, Ni Geng, Xiurui Zhao, Yongchao Tang, Hairong Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Science China Patent Examination Cooperation Center of State Intellectual Property Office 100190 China

ISBN: (纸本)9781457709692

The main goal of data fusion in remote sensing is integrating the respective superiority and complementary information of multi-source data to serve the applications. Most conventional fusion algorithm is oriented to fuse the multispectral (hyperspectral) data with panchromatic data such as IHS fusion, PCA fusion, DWT fusion, Brovey fusion etc. Although these methods have been widely used, they still have a problem that can't maintain the spatial information and spectral information synchronously. In this study, a new fusion algorithm aiming at fusing multispectral data and hyperspectral data was developed in following steps: First, classify the hyperspectral data into groups basing on the wavelength range of each multispectral band;second, process each band group by PCA, and combine all the first components to a new multispectral data;then, separate each original multispectral pixel by the homologous pixel and its eight neighbor pixels in the new multispectral data;Finally, mix the homologous 9 pixels of hyperspectral data by the abundance got by former step. The applying on AVIRIS data 'cuprite' brought by ENVI shows an excellent result and verified the validity. © 2011 IEEE.

关键词： Pixels

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Matrix calculation of high-dimensional cross product and its application in automatic recognition of the endmembers of hyperspectral imagary

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Science China(information Sciences) 2011年第1期54卷 197-203页

作者： GENG XiuRui1,ZHAO YongChao1,LIU SuHong2 & WANG FuXiang3 1key laboratory of technology in geo-spatial information processing and Application System, Institute of Electronics,Chinese Academy of Sciences,Beijing 100080,China 2State key laboratory of Remote Sensing Science,Jointly Sponsored by Beijing Normal University and the Institute of Remote Sensing Applications of Chinese Academy of Sciences, School of geography,Beijing Normal University,Beijing 100875,China 3School of Electronics and information Engineering,Beihang University,Beijing 100191,China 1. Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing 100080 China2. State Key Laboratory of Remote Sensing Science Jointly Sponsored by Beijing Normal University and the Institute of Remote Sensing Applications of Chinese Academy of Sciences School of Geography Beijing Normal University Beijing 100875 China3. School of Electronics and Information Engineering Beihang University Beijing 100191 China

This paper gives the definition of the high-dimensional cross product and its calculation by extending the 3-D cross product definition into the high-dimensional vector *** on the properties of the cross product,the volume variance index(VVI)is proposed to be used in extracting automatically the endmembers of the hypherspectral imagery which eliminates the shortcoming of the traditional method of using simplex only where the extraction results were easily impacted by the abnormal pixels.A case study of endmembers extraction experiment using the VVI method with the AVIRIS data for Cuprite has shown a very good result.

关键词： endmember simplex hyperspectral imagery cross product

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