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Remote sensing image enhancement based on relative entropy and fuzzy algorithm

Journal of Applied Sciences 2013年第13期13卷 2394-2398页

作者： Yang, Bo Jia, Zhen-Hong Qin, Xi-Zhong Yang, Jie Hu, Ying-Jie College of Information Science and Engineering Xinjiang University Urumqi 830046 China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China Knowledge Engineering and Discovery Research Institute Auckland University of Technology Auckland 1020 New Zealand

An improved maximum between-cluster variance (OTSU) algorithm was proposed to obtain the threshold adaptively in order to overcome the disadvantages of traditional Pal-King algorithm. The algorithm is able to globally enhance the remote sensing images but, for the relevance of neighboring pixel information is not taken into account in the improved algorithm, the visual effect of low contrast images is also not so good. The algorithm in this study can be used to realize the self-adaptive contrast enhancement when the relative entropy is regarded as a criterion. In order to test the enhancement effect of the proposed algorithm for remote sensing image, we choose 50 remote sensing images for test. Experimental results show that a good visual effect is obtained and the clarity, standard deviation has been improved greatly. Therefore, the algorithm is thought to be an effective ways to get better visual effects and more obvious detailed information. © 2013 Asian Network for Scientific information.

关键词： image enhancement

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Contour segmentation based on GVF snake model and contourlet transform 1

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9th International Conference on Intelligent Computing, ICIC 2013

作者： Zhang, Xinhong Cai, Kun Zhang, Fan Li, Rui Institute of Image Processing and Pattern Recognition Henan University Kaifeng 475001 China Software School Henan University Kaifeng 475001 China College of Computer and Information Engineering Henan University Kaifeng 475001 China

ISBN: (数字)9783642394829

ISBN: (纸本)9783642394812

A contour segmentation algorithm is proposed based on GVF Snake model and Contourlet transform. Firstly, object contours of images can be obtained based on Contourlet Transform, and those contours will be identified as the initial contour of GVF Snake model. Secondly, GVF Snake model is used to detect the contour edge of human gait motion. Experimental results show that the proposed method can extract the edge feature accurately and efficiently. © 2013 Springer-Verlag.

关键词： Contourlet transform

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Robust visual tracking based on online learning of joint sparse dictionary

Robust visual tracking based on online learning of joint spa...

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6th International Conference on Machine Vision, ICMV 2013

作者： Li, Qiaozhe Qiao, Yu Yang, Jie Bai, Li Key Laboratory of Ministry of Education for System Control and Information Processing Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China School of Computer Science University of Nottingham Nottingham United Kingdom

ISBN: (纸本)9780819499967

In this paper, we propose a robust visual tracking algorithm based on online learning of a joint sparse dictionary. The joint sparse dictionary consists of positive and negative sub-dictionaries, which model foreground and background objects respectively. An online dictionary learning method is developed to update the joint sparse dictionary by selecting both positive and negative bases from bags of positive and negative image patches/templates during tracking. A linear classifier is trained with sparse coefficients of image patches in the current frame, which are calculated using the joint sparse dictionary. This classifier is then used to locate the target in the next frame. Experimental results show that our tracking method is robust against object variation, occlusion and illumination change. © 2013 SPIE.

关键词： E-learning

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Improved DV-hop localization algorithm based on RSSI value and hop correction

Improved DV-hop localization algorithm based on RSSI value a...

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6th China Conference of Wireless Sensor Networks, CWSN 2012

作者： Guo, Zhengwei Min, Lin Li, Hui Wu, Wenjian School of Computer and Information Engineering Institute of Image Processing and Pattern Recognition Henan University Kaifeng Henan 475001 China Network Information Center Office Henan University Kaifeng Henan 475001 China Henan University Minsheng College Kaifeng Henan 475004 China

ISBN: (纸本)9783642362514

On the basis of the analysis of the relation between network's topologyand localization precisionan improved DV-Hop algorithm based on hop correction is put forward. Firstly, RSSI value is used to correct the distance between unknown node and reference nodes in the range of single hop;secondly, a certain amount of correction value is added to the original hop between unknown node and reference nodes to further reduce the distance error between them. Simulation result shows that improved algorithm improves the localization precision. © 2013 Springer-Verlag.

关键词： correction DV-Hop WSN

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Placement and selection algorithm of reference nodes in WSN localization

Placement and selection algorithm of reference nodes in WSN ...

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6th China Conference of Wireless Sensor Networks, CWSN 2012

作者： Min, Lin Li, Hui Guo, Zhengwei Network Information Center Office Henan University Kaifeng Henan 475001 China Henan University Minsheng College Kaifeng Henan 475004 China School of Computer and Information Engineering Institute of Image Processing and Pattern Recognition Henan University Kaifeng Henan 475001 China

ISBN: (纸本)9783642362514

Currently, few studies of wireless sensor network node localization algorithm were focused on the reference nodes, but how to choose and place reference nodes has a great influence on the positioning accuracy. In order to quantitatively study this issue, we proved a theorem, which describes the relationship between the placement of reference nodes and whether the node can be located, then the reference nodes placement method was designed. Finally, a reference nodes selection algorithm was proposed based on the condition number of linear equations, so as to improve the accuracy of range-based localization algorithm. © 2013 Springer-Verlag.

关键词： Number theory

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Robust adaptive beamforming method based on interference-plus-noise covariance matrix

Robust adaptive beamforming method based on interference-plu...

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2013 IEEE International Conference on Signal processing, Communications and Computing, ICSPCC 2013

作者： Hou, Yunshan Xue, Lin Jin, Yong College of Electronics and Information Engineering Henan University of Science and Technology Luoyang 471023 China College of Mathematics Luoyang Normal University Luoyang 471022 China Institute of Image Processing and Pattern Recognition Henan University KaiFeng 475000 China

ISBN: (纸本)9781479910274

In order to improve the performance of adaptive beamforming, this paper proposes a robust adaptive beamforming algorithm. In this algorithm, first the signal-free interference-plus-noise covariance matrix is reconstructed using MUSIC spatial spectrum as the power density distribution, then the optimization problem of estimating the desired signal steering vector is formulated by maximizing the array output power and adopting spherical set constraint, next the Lagrange multiplier method is employed to yield the computing formula of the optimal steering vector of desired signal. Simulation results demonstrate that the performance of proposed adaptive beamformer is almost always close to optimal in a very large range of signal-to-noise ratio(SNR), outperforming existing adaptive beamformers. © 2013 IEEE.

关键词： Signal to noise ratio

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Multi-feature bio-inspired model for scene classification

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Applied Mechanics and Materials 2013年 303-306卷 1569-1572页

作者： Hu, De-Kun Lin, Jie College of Information Science and Technology Chengdu University Chengdu 610106 China Key Laboratory of Pattern Recognition and Intelligent Information Processing Institutions of Higher Education of Sichuan Province 610106 China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 610054 China

ISBN: (纸本)9783037856529

A multi-feature bio-inspired model for scene image classification (MFBIM) is presented in this work;it extends the hierarchical feedforward model of the visual cortex. Firstly, each of three paths of classification uses each image property (i.e. shape, edge or color based features) independently. Then, BPNN assigns the category of an image based on the previous outputs. Experiments show that the model boosts the classification accuracy over the shape based model. Meanwhile, the proposed approach achieves a high accuracy comparable to other reported methods on publicly available color image dataset. © (2013) Trans Tech Publications, Switzerland.

关键词： computer vision

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Dynamic monitoring technique for remote-sensing image of invasive alien plant species

Dynamic monitoring technique for remote-sensing image of inv...

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2013 International Conference on Geo-Informatics in Resource Management and Sustainable Ecosystem, GRMSE 2013

作者： Hesen, Rabigul Jia, Zhenhong Yang, Jie Hu, Raphael College of Information Science and Engineering Xinjiang University Urumqi 830046 China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China Knowledge Engineering and Discovery Research Institute Auckland University of Technology Auckland 1020 New Zealand

ISBN: (纸本)9783642419072

Invasive Alien Plant Species (IAPS) could seriously affect the local ecosystem balance, and pose a threat to the ecological security. In order to effectively monitor and control invasive alien plants, it needs to monitor the spatial distribution and dynamic changes of IAPS. It will cite the method of nonsubsampled contourlet transform (NSCT) combination with fuzzy C-means clustering algorithm in this paper, which is used in remote sensing image change detection, for monitoring the dynamic changes of biological invasive species in this paper, to get a better detection result. © Springer-Verlag Berlin Heidelberg 2013.

关键词： image enhancement

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Novel change detection method based on direction feature and fuzzy clustering for remote sensing images and its application in biological invasions

Novel change detection method based on direction feature and...

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2013 International Conference on Geo-Informatics in Resource Management and Sustainable Ecosystem, GRMSE 2013

作者： Li, Qingsong Qin, Xizhong Jia, Zhenhong Yang, Jie Hu, Raphael College of Information Science and Engineering Xinjiang University 830046 Urumqi China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University 200240 Shanghai China Knowledge Engineering and Discovery Research Institute Auckland University of Technology 1020 Auckland New Zealand

ISBN: (纸本)9783642419072

Change detection techniques attempt to be used for remote sensing monitoring of invasive plants. A novel change detection method based on direction feature and RFLICM (an improved fuzzy C-means clustering) is proposed. Firstly, the difference image is acquired from multitemporal images. The pixel values of the difference image are updated using the template of directional neighborhood based on direction feature. The final change detection map is achieved by clustering the pixel values of the difference image using RFLICM algorithm into two disjoint classes: changed and unchanged. The results obtained by experiment are compared with some other existing state of the art methods. It is observed that the proposed method outperforms the other methods. Finally, the proposed change detection technique is applied to remote sensing monitoring of invasive plants. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Change detection

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Patching Method for Coverage Holes with Distance-Assistant in Wireless Sensor Networks

Patching Method for Coverage Holes with Distance-Assistant i...

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2013 International Conference on computer,Networks and Communication engineering(ICCNCE 2013)

作者： Zhengwei Guo Lin Zhu Department of Computer and Information Engineering Institute of Image Processing and Pattern Recognition Henan University Department of Computer and Information Technology Shangqiu Normal University

ISBN: (纸本)9781629932170

An effective approach for coverage holes was proposed, called Distance-assistant Coverage Hole Parching (DACHP) strategy. DACHP strategy would achieve the purpose of patching coverage holes using redundant sensor nodes within the wireless sensor networks. Simulation results show, compared with DFNFP and random algorithm, for the same size and shape coverage hole, DACHP can awaken five redundant nodes to patch 92.19% of hole, yet DFNFP needs awaken nine redundant nodes and just patch 90.28%. It can be seen that DFNFP not only awaken four extra nodes, but also is lower 1.19% in patching rate of hole than DACHP. In addition, DACHP is more stable in utilization of redundant nodes and does not produce additional cost.

关键词： wireless sensor networks coverage holes patching holes nodes utiliza

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