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

共 707 条记录，以下是371-380 订阅

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Contour-based feature extraction for image potential energy theory

Contour-based feature extraction for image potential energy ...

引用

2010 2nd iiTA conference on Geoscience and remote sensing, iiTA-GRS 2010

作者： Chen, Xuesong Xu, Xuejun Wang, Cheng Zhu, Hongbo Jiang, Shaohua Digital Engineering Simulation Center Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781424485154

A good feature extraction method can improve the performance of pattern recognition system or classification system. The contour can better to retain the original features of the object. In target recognition system, using potential energy of contour-point projection into the plane coordinate system. The method can be better to show a contour in the structural feature. In addition, it's better avoid the matrix storage redundancy. In all energy projection method, potential energy projection is better show its superiority in the structure information, the time of consumption and the storage space. Using potential energy theory into binary image feature extraction and feature store is a new method for image processing. Potential energy is to compute the energy of each pixel the first, and store the energy in order, which is better to retain the image features, and facilitate storage and classification. Contour is one of the most important features for distinguish between two objects. The contour potential energy can be used in target recognition and target classification field and so on. © 2010 IEEE.

关键词： Feature extraction

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Human visual system based processing for high resolution remote sensing image segmentation

Human visual system based processing for high resolution rem...

引用

2010 2nd International conference on Signal processing Systems, ICSPS 2010

作者： Wang, Guizhou He, Guojin Center for Earth Observation and Digital Earth Chinese Academy of Sciences Graduate University of Chinese Academy of Sciences Beijing China Center for Earth Observation and Digital Earth Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781424468911

image segmentation is very essential and critical to image processing and pattern recognition. Watershed is the most popular one among all the proposed image segmentation algorithms, but it suffers from over-segmentation. To resolve the over-segmentation problem and obtain a concise region representation has been the focus of many researchers. There are many ways to reduce the over-segmentation. However, Human visual system (HVS) is often not incorporated into the consideration and process of segmentation. This paper presents a new approach to high resolution remote sensing image segmentation taking into consideration human visual system (HVS) model. A Contrast Sensitivity Function (CSF) based filtering is applied to the image before watershed transform. Multi-scale spatial frequency filtering images are derived from setting multi-scale viewing distance. Then the region merging based on Just Noticeable Difference (JND) is applied to the segmentation results. Finally, the effect of reducing over-segmentation based on CSF and JND is analyzed and significant improvement is reported in the experimental results. © 2010 IEEE.

关键词： image segmentation

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Perceptual grouping for building recognition from satellite SAR image stacks

Perceptual grouping for building recognition from satellite ...

引用

International conference on pattern recognition

作者： Michaelsen, E. Soergel, U. Schunert, A. Doktorski, L. Jaeger, Klaus Fraunhofer-IOSB Gutleuthausstrasse 1 76275 Ettlingen Germany IPI Leibniz Univ. Hannover Nienburger Str.1 30167 Hannover Germany

ISBN: (纸本)9781424472574

Modern high resolution satellite SAR sensors even allow analysis of building sub-structures like windows and balconies. In the amplitude data man-made objects usually appear either as salient bright lines or points embedded within dark background. The latter features may coincide also with so-called persistent scatterers (PS), whose phase history is exploited by time series analysis for 3D reconstruction and deformation monitoring. We apply principles of human gestalt perception for grouping urban objects such as entire facades. The analysis takes place both in the amplitude and the phase data. Fusion is possible at different levels, e.g: i) grouping results in one domain may focus search in the other domain, ii) both approaches allow to infer independently the 3D structure by exploiting complementary features (amplitude vs. phase), and iii) grouping as such is useful to introduce model knowledge. © 2010 IEEE.

关键词： Time series analysis

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image Registration Using Modified Adaptive Polar Transform

Image Registration Using Modified Adaptive Polar Transform

引用

International conference and Exhibition on Biometrics Technology

作者： Sasikala, D. Neelaveni, R. Bannari Amman Inst Technol Dept Comp Sci & Engn Sathyamangalam 638401 Tamil Nadu India PSG Coll Technol Dept Elect & Elect Engn Coimbatore 641014 Tamil Nadu India

image registration is of great significance to medicine and remote sensing, so a lot of techniques have been developed within the context of one or the other discipline. This paper proposes an approach for medical image registration using Modified Gabor Wavelet Transform (MGWT) for Modified Adaptive Polar Transform (MAPT). This algorithm can be used to register images of the same or different modalities. This transform analyzes periodic signal components and presents the advantage of being independent of the window length. The performance of the Modified Gabor Wavelet Transform is compared with previous methods like Log Polar Transform and Adaptive Polar Transform. The results show that MGWT outperforms all evaluated model-independent methods with respect to identification accuracy. These results show that the basis of errors produced by the previous methods is the fixed working scale. The new method not only avoids this basis of errors but also makes a tool available for detailed study. (C) 2010 Published by Elsevier Ltd

关键词： Sequence analysis wavelet transform coding regions signal processing pattern recognition

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A high performance fully pipelined architecture for lossless compression of satellite image

A high performance fully pipelined architecture for lossless...

引用

2010 International conference on Multimedia Technology, ICMT 2010

作者： Wang, Ze Zhang, Tianxu Yan, Luxin Gong, Cheng State Key Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781424478743

This paper presents a novel hardware implementation of the adaptive JPEG-LS in field programmable gate array (FPGA), based on the low complexity lossless compression for images (LOCO-I) compression scheme. Differently from what previously reported in literature, this design achieves a much lower complexity and super high data throughput through an improved prediction model by breaking the feedback loop of context parameters updating. The processing speed of this design is up to 75Mpixels per second, while the compression ratio is slightly lower than the standard JPEG-LS compression. Performance evaluation also indicates that design complexity and compression efficiency can be taken account at the same time to achieve satisfactory result. Such an implementation could be used for high-speed compression of satellite remote sensing image onboard. ©2010 IEEE.

关键词： image compression

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Design and implementation of knowledge base for target recognition in remote sensing images

Design and implementation of knowledge base for target recog...

引用

International conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Shaobin Chen Chao Cai Erlang Li Mingyue Ding Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology China School of Life Science and Technology Huazhong University of Science and Technology Wuhan China

In this paper, the knowledge modeling, architecture design and detailed implementation of an ontology-based knowledge base for target recognition in remote sensing images is presented. Knowledge base is a critical component of a large ground target recognition system which is a hybrid system that combines knowledge base with remote sensing image processing module. The knowledge base provides necessary knowledge for remote sensing image processing module, and remote sensing image processing module can perform multiple tasks with the support of the knowledge base. The existence of the knowledge base makes the whole recognition system more flexible and more generic than those systems without knowledge base. The effectiveness of the presented knowledge base shows the good prospect of the application of knowledge base in remote sensing image processing domain.

关键词： Knowledge based systems Target recognition remote sensing OWL Ontologies Semantics

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An Adaptive Level Set Model with Feature Selection for remote sensing image Segmentation

An Adaptive Level Set Model with Feature Selection for Remot...

引用

Chinese conference on pattern recognition (CCPR)

作者： Shijin Li Wanguo Wang Dingsheng Wan School of Computer and Information Engineering Hohai University HHU Nanjing China

An adaptive level set model with feature selection for remote sensing image segmentation is proposed. The traditional C-V Model based on level set pays much attention to the color features, but with less emphasis on texture features. In the processing of remote sensing image, sometimes texture feature is more important for the purpose of image segmentation. To solve the problem, this paper firstly takes the components of different color spaces and the texture features as the initial feature set. Then feature selection is performed through local similarity analysis. Meanwhile, the weights of different features are adjusted accordingly. The selected features are utilized in the C-V model as inputs to segment the remote sensing image. Experimental results on various remote sensing imagery show that the newly proposed approach not only outperforms the traditional model efficiently, but also reduces the time cost greatly.

关键词： Capacitance-voltage characteristics Level set image segmentation remote sensing image color analysis Active contours Computational modeling

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An adaptive level set model with feature selection for remote sensing image segmentation

An adaptive level set model with feature selection for remot...

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Chinese conference on pattern recognition

作者： Li, Shijin Wang, Wanguo Wan, Dingsheng School of Computer and Information Engineering Hohai University Nanjing 210098 China

ISBN: (纸本)9781424472109

关键词： image segmentation

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Application of Back Propagation Neural Network in the Classification of High Resolution remote sensing image Take remote sensing image of Beijing for instance

Application of Back Propagation Neural Network in the Classi...

引用

The 18th International conference on Geoinformatics(第18届国际地理信息科学与技术大会 Geoinformatics 2010)

作者： Jiefeng Jiang Jing Zhang Gege Yang Dapeng Zhang Lianjun Zhang Key Laboratory of 3D Information Acquisition and Application of Ministry of Education Capital Normal University BeijingChina

ISBN: (纸本)9781424473014

In recent years, the development of high-resolution remote sensing image extends the visual field of the terrain features. Quickbird and other high-resolution remote sensing image can show more characteristics such as shape, spectral, texture and so on. Back Propagation neural network is widely used in remote sensing image classification in recent years, it is a self-adaptive dynamical system which is widely connected by large amount of neural units, and it bases on distributing store and parallel processing. It study by exercise and had the capacity of integrating the information, synthesis reasoning, and rapid overall processing capacity. It can solve the regular problem arise from remote sensing image processing, therefore, it is widely used in the application of remote sensing. This paper discusses the Back Propagation neural network method in order to improve the high resolution remote sensing image classification precision. By analyzing the principle and learning algorithms of Back Propagation neural network, we utilize the Quickbird imagery of Beijing with high resolution as experimental data and do the research of road and simple building roof, In this paper, the use of remote sensing image processing software Matlab, and then combined with Back Propagation neural network classifier for the high resolution remote sensing images of their pattern recognition.

关键词： Back Propagation neural network:high-resolution remote sensing image:classification Introduction

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Contour-based feature extraction for image potential energy theory

Contour-based feature extraction for image potential energy ...

引用

iiTA International conference on Geoscience and remote sensing (iiTA-GRS)

作者： Xuesong Chen Xuejun Xu Cheng Wang Hongbo Zhu Shaohua Jiang Digital Engineering Simulation Center Huazhong University of Science and Technology Wuhan China

A good feature extraction method can improve the performance of pattern recognition system or classification system. The contour can better to retain the original features of the object. In target recognition system , using potential energy of contour-point projection into the plane coordinate system. The method can be better to show a contour in the structural feature. In addition, it's better avoid the matrix storage redundancy. In all energy projection method, potential energy projection is better show its superiority in the structure information, the time of consumption and the storage space. Using potential energy theory into binary image feature extraction and feature store is a new method for image processing. Potential energy is to compute the energy of each pixel the first, and store the energy in order, which is better to retain the image features, and facilitate storage and classification. Contour is one of the most important features for distinguish between two objects. The contour potential energy can be used in target recognition and target classification field and so on.

关键词： image resolution Energy resolution Support vector machines image recognition Biology

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