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2007 1st Asian and Pacific Conference on Synthetic Aperture Radar, APSAR 2007

作者： Zhu, Jiabing Chen, Renyuan Hong, Yi East China Research Institute of Electronic Engineering China Education Ministry Key Lab. of Intelligent Computing and Signal Processing Anhui University China

ISBN: (纸本)1424411882

The novel adaptive filtering algorithm based on the analysis of the detail images obtained from the wavelet decomposition of the original noisy image is proposed in the paper. The base idea is to compute the wavelet decomposition of the noisy image to reduce the amplitude of insignificant detail coefficients in the wavelet subspaces by selecting an adaptive filter window of size, the adaptive windowing algorithm was introduced where the window size is automatically adjusted depending on the samples statistics in the boundary of this window such as mean z and standard deviation σz, and then utilizing modified 2nd order Lee filtering. One of the advantages of this approach over the traditional speckle filtering method is the fact that textures are preserved while speckle is reduced. Experimental simulations by real SAR images show it are effective. © 2007 IEEE.

关键词： Wavelet decomposition

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New algorithm of target classification in polarimetric SAR

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Journal of Systems Engineering and Electronics 2008年第2期000卷

作者： Wang Yang Lu Jiaguo Wu Xianliang Wang Yang (Key Lab of Intelligent Computing & Signal Processing of Ministry of Education Anhui Univ. Heifei 230039 P. R. China The 38th Research Inst. China Electronic Technology Corporation Hefei 230031 P. R. China) Lu Jiaguo (The 38th Research Inst. China Electronic Technology Corporation Hefei 230031 P. R. China) Wu Xianliang (Key Lab of Intelligent Computing & Signal Processing of Ministry of Education Anhui Univ. Heifei 230039 P. R. China)

The different approaches used for target decomposition (TD) theory in radar polarimetry are reviewed and three main types of theorems are introduced: those based on Mueller matrix, those using an eigenvector analysis of the coherency matrix, and those employing coherent decomposition of the scattering matrix. Support vector machine (SVM), as a novel approach in pattern recognition, has demonstrated success in many fields. A new algorithm of target classification, by combining target decomposition and the support vector machine, is *** conduct the experiment, the polarimetric synthetic aperture radar (SAR) data are used. Experimental results show that it is feasible and efficient to target classification by applying target decomposition to extract scattering mechanisms, and the effects of kernel function and its parameters on the classification efficiency are significant.

关键词： polarimetric synthetic aperture radar target decomposition support vector machine target classifi-cation kernel function.

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Multirracial and R/S analysis of protein structure

Multirracial and R/S analysis of protein structure

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SNPD 2007: 8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed computing

作者： Zheng, Tingting Cheng, Jiaxing Mao, Junjun Song, Jie Key Lab. of Intelligent Computing and Signal Processing Anhui University Hefei 230039 China School of Mathematics and Computational Science Anhui University Hefei 230039 China

ISBN: (纸本)0769529097

The spacing distance of amino acids is used to study the relationship between the primary structure and structural classification of large proteins. Rescaled-range (R/S) analysis was adopted to examine long-range correlation property of proteins. And multifractal property is then discussed by the spacing distance of amino acids. A classification of proteins by assigning to each sequence a point in two-dimensional space (Δα, H) is given to construct a phylogenetic tree. This result is shown to be reasonably satisfactory to α + β class. © 2007 IEEE.

关键词： Proteins

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Urban road network extraction from SAR image

Urban road network extraction from SAR image

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MIPPR 2007: Remote Sensing and GIS Data processing and Applications;and Innovative Multispectral Technology and Applications

作者： Cheng, Pengxue Hu, Maolin Lab. of Intelligent Computing and Signal Processing Anhui University Hefei Anhui 230039 China Key Laboratory of Wireless Sensor Network and Communication Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai 200050 China

ISBN: (纸本)9780819469540

In this paper, a technique for the extraction of roads in a high resolution synthetic aperture radar (SAR) image is presented. And a three-step method is developed for the extraction of road network from space borne SAR image: the process of the feature points, road candidate detection and connection. Roads in a high resolution SAR image can be modeled as a homogeneous dark area bounded by two parallel boundaries. Dark areas, which represent the candidate positions for roads, are extracted from the image by a Gaussian probability iteration segmentation. Possible road candidates are further processed using the morphological operators. And the roads are accurately detected by Hough Transform, and the extraction of lines is achieved by searching the peak values in Hough Space. In this process, to detect roads more accurately, post-processing, including noisy dark regions removal and false roads removal is performed. At last, Road candidate connection is carried out hierarchically according to road established models. Finally, the main road network is established from the SAR image successfully. As an example, using the ERS-2SAR image data, automatic detection of main road network in Shanghai Pudong area is presented.

关键词： Feature extraction

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Point matching of two images under large different resolution

Point matching of two images under large different resolutio...

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MIPPR 2007: Automatic Target Recognition and Image Analysis;and Multispectral Image Acquisition

作者： Ruan, Lei Hu, Maolin Lab. of Intelligent Computing and Signal Processing AnHui University Hefei AnHui 230039 China Key Laboratory of Wireless Sensor Network and Communication Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai 200050 China

ISBN: (纸本)9780819469502

Image matching is the first step in almost any 3D computer vision task, and hence has received extensive attention. In this paper, the problem is addressed from a novel perspective, which is different from the classic stereo matching paradigm. Two images with different resolutions, that is high resolution versus low resolution are matched. Since the high resolution image only corresponds to a small region of the low resolution one, the matching task therefore consists in finding a small region in the low resolution image that can be assigned to the whole high resolution image under the plane similarity transformation, which can be defined by the local area correlation coefficient to match the interest points and rectified by similarity transform. Experiment shows that our matching algorithm can be used for scale changing up to a factor of 6. And it is successful to deal with the point matching between two images under large scale.

关键词： Image matching

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Good Lattice Swarm Algorithm for Constrained Engineering Design Optimization

Good Lattice Swarm Algorithm for Constrained Engineering Des...

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第三届IEEE无线通讯、网络技术暨移动计算国际会议

作者： Shoubao Su Jiwen Wang Wangkang Fan Xibing Yin Key Lab of Intelligent Computing & Signal Processing of the National Education Ministry Anhui Unive Key Lab of Intelligent Computing & Signal Processing of the National Education Ministry Anhui Unive Gear Institute of Lu'an Automotive Gear Manufacture Co. Ltd Anhui Jianghuai Automotive Group Lu'an

Engineering optimization in the intelligence swarm remains to be a challenge. Recently, a novel optimization method based on number-theory and particle swarm, good lattice swarm optimization algorithm(GLSO), is introduced, which intends to produce faster and better global search ability and more accurate convergence because it has a solid theoretical basis. In this paper, four models of constructing good point set are introduced and the GLSO based on new models is rewritten. Some applications of the new model on constrained engineering via employing a penalty function approach suggest that the presented algorithm is potentially a powerful search technique for solving complex engineering design optimization problems.

关键词： good lattice points particle swarm optimization constrained engineering optimization penalty function.

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Image Reconstruction Based on Sub-Gaussian Random Projection

Image Reconstruction Based on Sub-Gaussian Random Projection

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International Conference on Image and Graphics (ICIG)

作者： Hong Fong Quanbing Zhang Sui Wei College of Science Hefei University of Technology Hefei China Key Lab of Intelligent Computing and Signal Processing Anhui University Hefei China

In this paper, we introduce the sub-Gaussian random projection into compressed sensing (CS) theory and present two new kinds of CS measurement matrices: sparse projection matrix and very sparse projection matrix. By the tail bounds for sub-Gaussian random projection, we present the proof of how these new matrices satisfying the necessary condition for CS measurement matrix. Further, we expatiate that owe to their sparsity, new matrices greatly simplify the projection operation during images reconstruction, which greatly improves the speed of reconstruction. The results of simulated and real experiments show that with a certain number of measurements, new matrices both achieve good measurement effect and can acquire exact reconstruction by them. Last, the comparison of reconstruction results respectively adopting new matrices and Gaussian measurement matrix is conducted.

关键词： Image reconstruction Sparse matrices Compressed sensing Tail Couplings Graphics signal processing Educational institutions Linear programming Matrix decomposition

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Medical X-Ray Image Enhancement Based on Kramer's PDE Model

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Journal of Electronic Science and Technology of China 2007年第2期5卷 187-190页

作者： Yan-Fei Zhao Qing-Wei Gao De-Xiang Zhang Yi-Xiang Lu Key Lab. of Intelligent Computing and Signal Processing of MOE Anhui University. Hefei 230039 China School of Electronic Science and Technology Anhui University Hefei 230039 China

The purpose of this study is to present an application of a novel enhancement technique for enhancing medical images generated from X-rays. The method presented in this study is based on a nonlinear partial differential equation （PDE） model, Kramer＇s PDE model. The usefulness of this method is investigated by experimental results. We apply this method to a medical X-ray image. For comparison, the X-ray image is also processed using classic Perona-Malik PDE model and Catte PDE model. Although the Perona-Malik model and Catte PDE model could also enhance the image, the quality of the enhanced images is considerably inferior compared with the enhanced image using Kramer＇s PDE model. The study suggests that the Kramer＇s PDE model is capable of enhancing medical X-ray images, which will make the X-ray images more reliable.

关键词： Terms-Enhancement nonlinear partial differential equation （PDE） partial differential equation model X-ray image.

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Medical X-Ray Image Enhancement Based on Kramer's PDE Model

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Journal of Electronic Science and Technology 2007年第2期000卷 187-190页

作者： Y.-F.Zhao Q.-W.Gao D.-X.Zhang Y.-X.Lu Key Lab. of Intelligent Computing and Signal Processing of MOE Anhui University. Hefei 230039 China School of Electronic Science and Technology Anhui University Hefei 230039 China

The purpose of this study is to present an application of a novel enhancement technique for enhancing medical images generated from X-rays. The method presented in this study is based on a nonlinear partial differential equation (PDE) model, Kramer’s PDE model. The usefulness of this method is investigated by experimental results. We apply this method to a medical X-ray image. For comparison, the X-ray image is also processed using classic Perona-Malik PDE model and Catte PDE model. Although the Perona-Malik model and Catte PDE model could also enhance the image, the quality of the enhanced images is considerably inferior compared with the enhanced image using Kramer’s PDE model. The study suggests that the Kramer’s PDE model is capable of enhancing medical X-ray images, which will make the X-ray images more reliable.

关键词： Enhancement nonlinearpartialdifferentialequation(PDE) partialdifferentialequationmodel X-rayimage

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A novel image content authentication algorithm based on Laplace spectra feature

A novel image content authentication algorithm based on Lapl...

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26th Chinese Control Conference, CCC 2007

作者： Wanli, Lv Yutang, Guo LuoBin Key Lab of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 China Computer Department Anhui Institute of Education Hefei 230061 China

ISBN: (纸本)7900719229

A novel image content authentication algorithm based on Laplace spectra was proposed. Outstanding feature points are extracted from the original image and a cipher point is inserted. A relational graph is then built, and the Laplace spectra of the graph are calculated to serve as image features. The Laplace spectra are quantized then embedded into the original image as a watermark. In the authentication step, the Laplace spectra of the authenticating image are calculated and compared with that of the watermark embedded in the authenticating image. If both of the spectra are identical, the image passes the authentication test. Otherwise, the tamper is found. The experimental results show that the proposed authentication algorithm can effectively detect the event and the location when the original image content is tampered viciously.

关键词： Laplace equation

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