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2009 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2009

作者： Yang, Shuyuan Wu, Ruixia Meng, Huixiao Jiao, Licheng Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9781424427314

Synthetic aperture radar (SAR) data collections can cover large areas at high resolution, generating massive amounts of data. Many existed transform-based compression techniques can effectively reduce the costs of storage and transmission with slight loss of information. As a new developed multi-resolution geometry analysis tool, Bandelet can make full use of intrinsic geometry regularity of images and exhibit enormous potential in image compression. In this paper, we propose a low complexity Bandelet transform for SAR image compression. A new cost function is defined to determine the optimal geometric flows in each dyadic squared sub-block of images, and an optimization of low frequency component followed by EBCOT coding of the Bandelet coefficients are employed. Some experiments are taken on some Ku-band SAR images came from Sandia National Laboratories and the results show the superiority of our proposed method over JPEG2000 and the second generation Bandelet in PSNR, ENL and EPI. ©2009 IEEE.

关键词： Cost functions

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Detecting flood change with multitemporal SAR images based on difference images fusion and fuzzy degree of nearness

Detecting flood change with multitemporal SAR images based o...

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MIPPR 2009 - Automatic Target Recognition and image Analysis: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Li, Jinji Jiao, Licheng Zhang, Xiangrrong Hou, Biao Yang, Dongdong Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478061

In this paper, we present a novel approach for detecting the changed regions caused by flooding events in multi-temporal SAR images. And the proposed method concludes two parts: 1) constructing difference image (DI) by fusion strategy proposed in this paper;2) producing change-detection map based on FCM and fuzzy degree of nearness. Experimental comparisons on real multi-temporal SAR images indicate that the proposed method can reduce the affection by speckle noise. Meanwhile, the proposed method can accurately detect the interested changed regions. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Synthetic aperture radar

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Gene transposon based clonal selection algorithm for clustering

Gene transposon based clonal selection algorithm for cluster...

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11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009

作者： Liu, Ruochen Sheng, Zhengchun Jiao, Licheng Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9781605583259

Inspired by the principle of gene transposon proposed by Barbara McClintock, a new immune computing algorithm for clustering multi-class data sets named as Gene Transposition based Clone Selection Algorithm (GTCSA) is proposed in this paper, The proposed algorithm does not require a prior knowledge of the numbers of clustering;an improved variant of the clonal selection algorithm has been used to determine the number of clusters as well as to refine the cluster center. a novel operator called antibody transposon is introduced to the framework of clonal selection algorithm which can realize to find the optimal number of cluster automatically. The proposed method has been extensively compared with Variable-string-length Genetic Algorithm(VGA)based clustering techniques over a test suit of several real life data sets and synthetic data sets. The results of experiments indicate the superiority of the GTCSA over VGA on stability and convergence rate, when clustering multi-class data sets. Copyright 2009 ACM.

关键词： Genes

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Quantum-inspired evolutionary clustering algorithm based on manifold distance 09

Quantum-inspired evolutionary clustering algorithm based on ...

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2009 World Summit on Genetic and Evolutionary Computation, 2009 GEC Summit - 1st ACM/SIGEVO Summit on Genetic and Evolutionary Computation, GEC'09

作者： Yangyang, Li Hongzhu, Shi Maoguo, Gong Ronghua, Shang Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9781605583266

Based on the concepts and principles of quantum computing, a quantum-inspired evolutionary algorithm for data clustering (QECA) is proposed in this paper. And a novel distance measurement index called manifold distance is introduced. These attribute data are the main source of clustering problem, due to its complex distribution, most clustering algorithms available are only suitable for these types of characteristic data. In this study, a new algorithm which can deal with these data with manifold distribution is more effective. The main motives of using QECA consist in searching for appropriate cluster center so that a similarity metric of clusters are optimized more quickly and effectively. The superiority of QECA over fuzzy c-means (FCM) algorithm and immune evolutionary clustering algorithm (IECA) is extensively demonstrated in our experiments. Copyright 2009 ACM.

关键词： Clustering algorithms

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Synthetic aperture radar automatic target recognition based on curvelet transform

Synthetic aperture radar automatic target recognition based ...

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MIPPR 2009 - Automatic Target Recognition and image Analysis: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Wang, Shuang Liu, Zhuo Jiao, Licheng He, Jun Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478061

A novel synthetic aperture radar (SAR) automatic target recognition (ATR) approach based on Curvelet Transform is proposed. However, the existing approaches can not extract the more effective feature. In this paper, our method is concentrated on a new effective representation of the moving and stationary target acquisition and recognition (MSTAR) database to obtain a more accurate target region and reduce feature dimension. Firstly, MSTAR database can be extracted feature through the optimal sparse representation by curvelets to obtain a clear target region. However, considering the loss of part of edges of image. We extract coarse feature, which is to compensate fine feature error brought by segmentation. The final features consisting of fine and coarse feature are classified by SVM with Gaussian radial basis function (RBF) kernel. The experiments show that our proposed algorithm can achieve a better correct classification rate. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Automatic target recognition

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SAR target recognition based on improved sparse LSSVM

SAR target recognition based on improved sparse LSSVM

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MIPPR 2009 - Automatic Target Recognition and image Analysis: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Zhang, Xiangrong Zhang, Yifan Jiao, Licheng Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478061

An Improved Fast Sparse Least Squares Support Vector Machine (IFSLSSVM) is proposed for Synthetic Aperture Radar (SAR) target recognition. Least Squares Support Vector Machine (LSSVM) is a least square version of Support Vector Machine (SVM), but it lacks the sparseness compared with SVM. IFSLSSVM, which combines the incremental learning and decremental learning, selects those important samples as the support vectors, and implements pruning by a certain condition, can solve the non-sparse problem of LSSVM effectively. Benchmarking UCI datasets are firstly used for testing the performance of our algorithm, followed by SAR target recognition. Experimental results on MSTAR SAR dataset show that IFSLSSVM is an effective SAR target recognition approach (SAR-ATR), which not only reduces the number of support vectors but also enhances the recognition rate. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Support vector machines

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Recoverable image watermarking based on halftoning for content authentication

Recoverable image watermarking based on halftoning for conte...

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MIPPR 2009 - Remote Sensing and GIS Data processing and Other Applications: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Wang, Zuxi Zhao, Xiangyuan Wang, Wenzong Hu, Hanping Li, Li Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology China Key Laboratory of Image Processing and Intelligent Control Ministry of Education Wuhan 430074 China

ISBN: (纸本)9780819478092

In this paper, a semi-fragile watermark solution based on quantization index modulation in the wavelet region was proposed. The algorithm employs a compressed halftoned binary image as watermark and embeds it in the wavelet domain through quantization index modulation, which can not only identify the authenticity of the content of digital image, but also recover the tampered image approximately. Because the watermark is a low-resolution original image, which carries the original image information, so the original image is not required when authenticating, and the tampered region can be recovered according to the watermark. The method can tolerate a certain degree of compression distortion or noise. Beside, a secret key is used to select the embedded watermark bits and their embedded positions to increase the security of watermarking. Experimental results show this semi-fragile watermarking algorithm is effective and practical for content authentication. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Binary images

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RETRACTED ARTICLE: Digital fingerprinting based on synergetic

RETRACTED ARTICLE: Digital fingerprinting based on synergeti...

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2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009

作者： Wang, Zuxi Ge, Qiang Wang, Wenzong Hu, Hanping Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control Ministry of Education Wuhan China

ISBN: (纸本)9781424445073

Owing to the weaknesses of existing correlation detection methods in digital fingerprint matching, such as difficult to determine the threshold and low matching accuracy rate, a method proposed in digital fingerprint matching based on synergetic, which was applied in pattern recognition. Then, the experimental result indicated that the method proposed in the paper has a high matching rate. ©2009 IEEE.

关键词： Copyrights

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A new change detection method based on non-parametric density estimation and Markov random fields

A new change detection method based on non-parametric densit...

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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Wang, Guiting Fan, Yuanzhang Jiao, Licheng Institute of Intelligent Information Processing Xidian University Xi'an 710071 China Key Laboratory of Intelligent Perception and Image Understanding Ministry of Education of China China

ISBN: (纸本)9780819478085

A new change detection approach based on non-parametric density estimation and Markov random fields is proposed in this paper. As the concrete form of gray statistical distribution of remote sensing images is often difficult to be known, the non-parameter density estimation method does not need the specific forms in advance, and is especially suitable for the estimation problem of small samples, so we adopt the non-parametric density estimation method to obtain the precise estimation of the probability density of statistical distribution of differencing image in the paper, and then perform multitemporal remote sensing image change detection combining with MRF(Markov random fields)model for spatial smoothing. The final experimental results show that the proposed method is effective. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Probability distributions

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基于第二代Bandelet域隐马尔可夫树模型的图像分割

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自动化学报 2009年第5期35卷 498-504页

作者：侯彪徐婧刘凤焦李成 Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

第二代Bandelet可以充分利用图像的内在几何正则性特点,并能自适应获得图像的最优表示.本文采用隐马尔可夫树(Hidden Markov tree,HMT)模型对图像的第二代Bandelet系数建模,通过多尺度参数训练和基于上下文的最大后验概率进行图像分割.... 详细信息

第二代Bandelet可以充分利用图像的内在几何正则性特点,并能自适应获得图像的最优表示.本文采用隐马尔可夫树(Hidden Markov tree,HMT)模型对图像的第二代Bandelet系数建模,通过多尺度参数训练和基于上下文的最大后验概率进行图像分割.为了评价本文方法的性能,我们分别选择合成纹理图像、航拍图像和SAR图像进行实验,并与小波域HMT模型分割方法(WD-HMTseg)和Contourlet域HMT模型分割方法(CHM Tseg)进行比较说明算法的有效性.实验结果表明本文方法不但在边缘准确性和区域一致性上有明显改进,而且也降低了纹理图的错分概率.

关键词：图像分割第二代Bandelet 隐马尔可夫树模型小波 Contourlet变换

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