检索结果-内蒙古大学图书馆

Blind source separation with unknown and dynamically changing number of source signals

Science in China(Series F) 2006年第5期49卷 627-638页

作者： YE Jimin ZHANG Xianda ZHU Xiaolong Key Laboratory for Radar Signal Processing Xidian University Xi'an 710071 China Department of Automation State Key Laboratory of Intelligent Technology and Systems Tsinghua University Beijing 100084 China

The contrast function remains to be an open problem in blind source separation （BSS） when the number of source signals is unknown and/or dynamically changed. The paper studies this problem and proves that the mutual information is still the contrast function for BSS if the mixing matrix is of full column rank. The mutual information reaches its minimum at the separation points, where the random outputs of the BSS system are the scaled and permuted source signals, while the others are zero outputs. Using the property that the transpose of the mixing matrix and a matrix composed by m observed signals have the indentical null space with probability one, a practical method, which can detect the unknown number of source signals n, ulteriorly traces the dynamical change of the sources number with a few of data, is proposed. The effectiveness of the proposed theorey and the developed novel algorithm is verified by adaptive BSS simulations with unknown and dynamically changing number of source signals.

关键词： blind source separation independent component analysis natural gradient mutual information contrast function neural networks.

来源：评论

学校读者我要写书评

暂无评论

SAR Image Despeckling Using Local Contextual Hidden Markov Model in the Contourlet Domain

SAR Image Despeckling Using Local Contextual Hidden Markov M...

引用

IEEE International Conference on radar

作者： Shuang Wang Xiao Xu Biao Hou Li Cheng Jiao Institute of Intelligent Information Processing and Key Laboratory for Radar Signal Processing Xidian University Xi'an China

Synthetic aperture radar (SAR) image despeckling is an important problem in the SAR applications. A novel despeckling approach using a local contextual hidden Markov model (LCHMM) in the contourlet domain is presented in this paper. The proposed method can not only use the multiresolution and multidirection characteristics of the contourlet transform, but also exploit the local statistics and capture the intrascale dependencies of the contourlet coefficients by using LCHMM. The experiments in despeckling SAR images show that the proposed method in contrary to other methods can obtain a better trade-off between smoothing the homogeneous areas and keeping the edges and can get better visual effect

关键词： Hidden Markov models Filter bank Synthetic aperture radar signal resolution Multiresolution analysis Wavelet transforms radar signal processing Statistics Smoothing methods Context modeling

来源：评论

学校读者我要写书评

暂无评论

SAR Image Compression Using Bandelets and SPIlT

SAR Image Compression Using Bandelets and SPIlT

引用

IEEE International Conference on radar

作者： Hanqiang Liu Biao Hou Shuang Wang Licheng Jiao Institute of Intelligent Information Processing and National Key Laboratory for Radar Signal Processing Xidian University Xi'an China

Synthetic aperture radar (SAR) image compression is very important in reducing the costs of data storage and transmission. A new compression scheme is proposed, which is composed of a multilayered image representation, bandelets and set partitioning in hierarchical trees (SPIHT) wavelet compression scheme. Firstly the SAR image is separated into cartoon and texture map using non-linear diffusion filter, then the SPIHT and bandelets coding methods are used to code the two layers independently. Experimental results show that our method outperforms JPEG, SPIHT and bandelets compression methods on the SAR image

关键词： Image coding Wavelet transforms Synthetic aperture radar Image representation Discrete wavelet transforms Wavelet coefficients Histograms Frequency Transform coding Statistics

来源：评论

学校读者我要写书评

暂无评论

Fusion of Multi-Sensor SAR Images via Adaptive Selection of Wavelet and Contourlet Coefficients

Fusion of Multi-Sensor SAR Images via Adaptive Selection of ...

引用

IEEE International Conference on radar

作者： Fan Liu Shuyuan Yang Licheng Jiao Institute of Intelligent Information Processing and National Key Laboratory for Radar Signal Processing Xidian University Xi'an China

Using SAR images of different spectral bands relative to the same scene can obtain a better knowledge of the scene than the one obtained using only one image. Fusing these images can provide more comprehensive information. In recent years, the fast growth of multiscale geometric analysis (MGA) has brought out abundant tools for image processing, such as curvelet and contourlet transform. In this paper, a novel fusion method based on adaptive selection of wavelet and contourlet coefficients is proposed for SAR image fusion. The main merit of the proposed method is that the wavelet transform can locate sparse of spot strangeness of SAR image effectively and contourlet transform can give a sparse representation of line strangeness, thus it can combine advantages of these tools, and get more details than other methods. The experimental results of four SAR images demonstrate that this algorithm performs better than classical fusion methods both in visual effect and object evaluation

关键词： Image fusion Synthetic aperture radar Wavelet transforms Layout Image analysis Pixel Image processing Wavelet analysis Wavelet packets radar signal processing

来源：评论

学校读者我要写书评

暂无评论

Remote Sensing Target Recognition Based on Contourlet and Kernel Fisher Discriminant

Remote Sensing Target Recognition Based on Contourlet and Ke...

引用

International Conference on Computational Intelligence and Security

作者： Rui Hu Licheng Jiao Weida Zhou Yi Gao Institute of Intelligent Information Processing and National Key Laboratory for Radar Signal Processing Xidian University Xi'an China

ISBN: (纸本)1424406048

An efficient feature extraction method for remote sensing target recognition was proposed in this paper, which was based on contourlet and kernel Fisher discriminant (KFD). After the contourlet decomposition, the contourlet features are fused (the weight for fusion is chosen by cross validation), and then KFD was used for further feature extraction, finally k-nearest-neighbor (KNN) was used for classification. Experimental results show that the proposed feature extraction method reach a higher correct rate than KFD and the method which use KFD on the lowpass filtered images. Moreover, when dealing with large scale images our method achieves a lower computation complexity than KFD

关键词： Remote sensing Target recognition Kernel Feature extraction Image recognition Filter bank Large-scale systems information processing Laboratories radar signal processing

来源：评论

学校读者我要写书评

暂无评论

Image Denoising Based on Second Generation Bandelets and Multi-level Thresholding

Image Denoising Based on Second Generation Bandelets and Mul...

引用

World Congress on intelligent Control and Automation (WCICA)

作者： Xiaohui Yang Wei Li Licheng Jiao National Key Laboratory for Radar Signal Processing and Institute of Intelligent Information Processing Xidian University Xi'an Shanxi China

As an updated multiresolution geometry analysis tool, second generation bandelets can make full use of intrinsic geometry regularity of images, and then provide an optimal representation of the underlying high-dimensional functions adaptively. In this paper, a novel approach to image denoising is presented, which is based on second generation bandelets and combined with multi-level thresholding. Numerical tests applied on natural images contaminated additive Gaussian white noise show that our method provides a significant improvement both in terms of image visual fidelity and in terms of peak signal-to-noise ratio. Comparisons are made with wavelet image noise-removal results

关键词： Image denoising signal resolution Geometry Spatial resolution Energy resolution Wavelet analysis Image resolution Image analysis Image processing Discrete transforms

来源：评论

学校读者我要写书评

暂无评论

APPROXIMATION MULTIDIMENSION FUCTION WITH FUNCTIONAL NETWORK

引用

Journal of Electronics(China) 2006年第1期23卷 81-84页

作者： Li Weibin Liu Fang Jiao Licheng Zhang Shuling Li Zongling Institute of Graphics and Image Processing Xianyang Normal University Xianyang 712000 China National Key Laboratory for Radar Signal Processing Xidian University Xi＇an 710071 China Insititute of Intelligent Information Processing Xidian University Xi＇an 710071 China

The functional network was introduced by ***, which extended the neural network. Not only can it solve the problems solved, but also it can formulate the ones that cannot be solved by traditional network. This paper applies functional network to approximate the multidimension function under the ridgelet theory. The method performs more stable and faster than the traditional neural network. The numerical examples demonstrate the performance.

关键词： Functional network Ridgelet Approximation

来源：评论

学校读者我要写书评

暂无评论

IMPROVED MLV FILTER TO REMOVE MULTIPLICATIVE NOISE

引用

Journal of Electronics(China) 2006年第1期23卷 85-88页

作者： Li Weibin Liu Fang Jiao Licheng Zhang Shuling Li Zongling Institute of Graphics and lmage Processing Xiangyang Normal University Xianyang 712000 China National Key Laboratory for Radar Signal Processing Xidian University Xi＇an 710071 China Insititute of lntelligent Information Processing Xidian University Xi＇an 710071China

More methods can be used to remove the additive noise, such as the Mean of Least Variance (MLV) filter. When the signal is noised by the multiplicative noise, it is difficult to remove. The paper presents an improved filter to remove multiplicative noise by changing the multiplicative noise to the additive noise, and then using the MLV-like to remove the additive noise. The simulation results show that the performance is better than Minimum Coefficient of Variation (MCV) filter and MLV filter. Both one-dimension and image experiments demonstrate its theoretical performance.

关键词： Denoising Minimum Coefficient of Variation （MCV） Mean of Least Variance （MLV）

来源：评论

学校读者我要写书评

暂无评论

A Novel Approach Based on Wavelet-ICA for SAR Image Speckle Suppression

A Novel Approach Based on Wavelet-ICA for SAR Image Speckle ...

引用

International Conference on signal processing Proceedings (ICSP)

作者： Xiaoguang Lu Ping Han Renbiao Wu Jingxiong Huang Tianjin Key Laboratory for Advanced Signal Processing Civil Aviation University of China Tianjin China ShenZhen Key Laboratory for Intelligent Information Processing ShenZhen University China

In this paper we propose a novel speckle suppression method based on the joint of wavelet transform (WT) and independent component analysis (ICA). The method employs ICA to process the wavelet coefficients of images, extracting the independent components which represent the uncorrupt images. Experimental results based on SAR (synthetic aperture radar) images of MSTAR (moving and stationary target acquisition and recognition) dataset show that the proposed method suppresses speckle effectively, and outperforms ICA and Lee filter

关键词： Speckle Independent component analysis Wavelet analysis Synthetic aperture radar Image analysis Wavelet transforms signal processing algorithms Discrete wavelet transforms signal processing Image recognition

来源：评论

学校读者我要写书评

暂无评论

Mean-shift blob tracking with adaptive feature selection and scale adaptation

Mean-shift blob tracking with adaptive feature selection and...

引用

14th IEEE International Conference on Image processing, ICIP 2007

作者： Dawei, Liang Qingming, Huang Shuqiang, Jiang Hongxun, Yao Wen, Gao School of Computer Science and Technology Harbin Institute of Technology Harbin 150001 China Graduate School Chinese Academy of Sciences Beijing 100080 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Institute of Digital Media Peking University Beijing 100871 China

ISBN: (纸本)1424414377

When the appearances of the tracked object and surrounding background change during tracking, fixed feature space tends to cause tracking failure. To address this problem, we propose a method to embed adaptive feature selection into mean shift tracking framework. From a feature set, the most discriminative features are selected after ranking these features based on their Bayes error rates, which are estimated from object and background samples. For the selected features, a criterion is proposed to evaluate their stability for tracking and to guide feature reselection. The selected features are used to generate a weight image, in which mean shift is employed to locate the object. Moreover, a simple yet effective scale adaptation method is proposed to deal with object changing in size. Experiments on several video sequences show the effectiveness of the proposed method. ©2007 IEEE.

关键词： Feature Selection

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：