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SAR image Despeckling Using Scale Mixtures of Gaussians in the Nonsubsampled Contourlet Domain

Chinese Journal of Electronics 2015年第1期24卷 205-211页

作者： CHANG Xia JIAO Licheng LIU Fang SHA Yuheng Institute of Image Processing and Understanding School of Mathematics and Information Science Beifang University of Nationalities Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China International Research Center for Intelligent Perception and Computation Xidian University School of Computer Science and Technology Xidian University

The edge and contour details in SAR images are important for subsequent processing tasks. The multiscale geometric analysis method — Nonsubsampled contourlet transform(NSCT) is able to capture the geometric information of SAR images effectively. Describing the aggregation behavior of the neighborhoods coefficients, the scale mixtures of Gaussians model has exhibited favorable performances. A novel SAR image despeckling method is presented by constructing the scale mixtures of Gaussians model of NSCT. This method models the SAR images using the multiscale and multidirection information in NSCT domain. The dependency relationship of NSCT neighborhoods coefficients are also taken into consideration in our model. The speckle noise coefficients are shrinkaged by statistical prior estimation based on SAR image model constructed. Experimental results demonstrate that our method is advantageous at directional information preservation and the speckle restraint.

关键词： Synthetic aperture radar(SAR) image despeckling Stationary wavelet transform Nonsubsampled contourlet transform Scale mixtures of Gaussians model.

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image matching navigation based on fuzzy information

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Journal of Harbin Institute of Technology(New Series) 2003年第4期10卷 447-449页

作者：田玉龙吴伟仁田金文柳健 State Key Laboratory for Image Processing and Intelligence Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology

In conventional image matching methods, the image matching process is mostly based on image statistic information. One aspect neglected by all these methods is that there is much fuzzy information contained in these images. A new fuzzy matching algorithm based on fuzzy similarity for navigation is presented in this paper. Because the fuzzy theory is of the ability of making good description of the fuzzy information contained in images, the image matching method based on fuzzy similarity would look forward to producing good performance results. Experimental results using matching algorithm based on fuzzy information also demonstrate its reliability and practicability.

关键词： image matching fuzzy information similarity

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A camera self-calibration method based on dual constraints of multi-view images

A camera self-calibration method based on dual constraints o...

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2011年无线通信与信号处理国际会议(WCSP 2011)

作者： Feng Liu Weiwei Han Qiong Xu Jingjing Fan Qiongjie Lin Image Processing and Image Communication Jiangsu Key Laboratory Key Lab of Broadband Wireless Commun Image Processing and Image Communication Jiangsu Key Laboratory

Camera calibration is the essential step of obtaining 3D information from 2D views in the field of computer vision, which is widely used in the area of 3D reconstruction, navigation, visual supervision, etc. A camera self-calibration method based on dual constraints of multi-view images is proposed to make calibration possible when there is no reference calibration block or the movement of camera is arbitrary. In this method, multi-view images are preprocessed first to select three images which are most suitable for camera self-calibration, then we use the method based on the genetic algorithm, the camera parameters are finally estimated by using epipolar geometry matching error and reprojection error as fitness functions as two steps. Experimental results show that the proposed camera self-calibration method is correct and effective.

关键词： multi-view images camera calibration dual constraints genetic algorithm epipolar geometry reprojection error

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Perspective for aggregation-induced delayed fluorescence mechanism:A QM/MM study

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Chinese Physics B 2020年第8期29卷 531-537页

作者： Jie Liu Jianzhong Fan Kai Zhang Yuchen Zhang Chuan-Kui Wang Lili Lin Key Laboratory of Medical Physics and Image Processing&Shandong Provincial Engineering and Technical Center of Light Manipulations School of Physics and ElectronicsShandong Normal UniversityJinan 250358China

To enhance the potential application of thermally activated delayed fluorescence(TADF)molecular materials,new functions are gradually cooperated to the TADF *** induced emission can effectively solve the fluorescence quenching problem for TADF molecules in solid phase,thus aggregation-induced delayed fluorescence(AIDF)molecules were recently ***,their luminescent mechanisms are not clear *** this work,excited state properties of an AIDF molecule DMF-BP-DMAC[reported in Chemistry-An Asian Journal 14828(2019)]are theoretically studied in tetrahydrofuran(THF)and solid *** consideration of surrounding environment,the polarizable continuum method(PCM)and the combined quantum mechanics and molecular mechanics(QM/MM)method were applied for solvent and solid phase,*** to the increase of the transition dipole moment and decrease of the energy difference between the first single excited state(S1)and the ground state(S0),the radiative rate is increased by about 2 orders of magnitude in solid *** energy dissipation of the non-radiative process from S1 to S0 is mainly contributed by low-frequency vibrational modes in solvent,and they can be effectively suppressed in aggregation,which may lead to a slow non-radiation process in solid *** factors would induce enhanced luminescence efficiency of DMF-BP-DMAC in solid ***,the small energy gap between S1 and triplet excited states results in high reverse intersystem crossing(RISC)rates in both solvent and solid ***,TADF is confirmed in both *** significantly influences both the ISC and RISC processes and more RISC channels are involved in solid *** enhanced delayed fluorescence should be induced by both the enhanced fluorescent efficiency and ISC *** calculation provides a reasonable explanation for experimental measurements and helps one to better understand the luminescence mechanism of AIDF molecules.

关键词： thermally activated delayed fluorescence aggregation-induced delayed fluorescence the combined quantum mechanics and molecular mechanics method

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A maximum a posteriori super resolution algorithm based on multidimensional Lorentzian distribution

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2009年第12期10卷 1705-1713页

作者： Wen CHEN Xiang-zhong FANG Yan CHENG Shanghai Key Lab of Digital Media Processing and Transmissions Institute of Image Communication and Information Processing Shanghai Jiao Tong University Shanghai 200240 China College of Information Technology East China University of Political Science and Law Shanghai 201620 China

This paper presents a threshold-free maximum a posteriori (MAP) super resolution (SR) algorithm to reconstruct high resolution (HR) images with sharp edges. The joint distribution of directional edge images is modeled as a multidimensional Lorentzian (MDL) function and regarded as a new image prior. This model makes full use of gradient information to restrict the solution space and yields an edge-preserving SR algorithm. The Lorentzian parameters in the cost function are replaced with a tunable variable, and graduated nonconvexity (GNC) optimization is used to guarantee that the proposed multidimensional Lorentzian SR (MDLSR) algorithm converges to the global minimum. Simulation results show the effectiveness of the MDLSR algorithm as well as its superiority over conventional SR methods.

关键词： Edge preservation Multidimensional Lorentzian distribution （MDL） Super resolution Threshold

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A novel method of constructing high-dimensional digital chaotic systems on finite-state automata

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Chinese Physics B 2020年第9期29卷 233-243页

作者： Jun Zheng Han-Ping Hu School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Image Information Processing and Intelligent Control Ministry of EducationWuhan 430074China

When chaotic systems are implemented on finite precision machines, it will lead to the problem of dynamical degradation. Aiming at this problem, most previous related works have been proposed to improve the dynamical degradation of low-dimensional chaotic maps. This paper presents a novel method to construct high-dimensional digital chaotic systems in the domain of finite computing precision. The model is proposed by coupling a high-dimensional digital system with a continuous chaotic system. A rigorous proof is given that the controlled digital system is chaotic in the sense of Devaney's definition of chaos. Numerical experimental results for different high-dimensional digital systems indicate that the proposed method can overcome the degradation problem and construct high-dimensional digital chaos with complicated dynamical properties. Based on the construction method, a kind of pseudorandom number generator (PRNG) is also proposed as an application.

关键词： high-dimensional digital chaotic system dynamical degradation anti-control pseudorandom number generator

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Re-ranking image search results by multiscale visual saliency model

Re-ranking image search results by multiscale visual salienc...

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2010 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2010

作者： Huang, Jun Yang, Xiaokang Zhang, Rui Fang, Xiangzhong Institute of Image Communication and Information Processing Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9781424444625

The paper focuses on two mechanisms, multiscale relevance and visual saliency, in web image search. First, in most current web image search engines, such as Google image Search, Yahoo image Search and so on, people judge the relevance of search results by the thumbnails and then click through the thumbnails to check if the corresponding image is really relevant. Basically the thumbnail and the corresponding image give the multiscale representations of the image. The second is that from visual point of view, it is obvious that salient images would be easier to catch users' eyes and more likely to be clicked than cluttered ones in low-level vision. In this paper, we build a multiscale saliency model and apply it to re-rank the results from web image search engines. Experimental results show that the model can achieve an average precision (AP) [1] of as high as 97%, and it improves the results of Google image search significantly.

关键词： Search engines

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Unequal decoding power allocation for efficient video transmission

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Journal of Shanghai University(English Edition) 2010年第1期14卷 60-65页

作者：王永芳余松煜杨小康张兆杨 Key Laboratory of Advanced Display and System Application School of Communication and Information Engineering Shanghai University Institute of Image Communication and Information Processing Research Shanghai Jiao Tong University

We present an unequal decoding power allocation （UDPA） approach for minimization of the receiver power consumption subject to a given quality of service （QoS）, by exploiting data partitioning and turbo decoding. We assign unequal decoding power of forward error correction （FEC） to data partitions with different priority by jointly considering the source coding, channel coding and receiver power consumption. The proposed scheme is applied to H.264 video over additive white Gaussion noise （AWGN） channel, and achieves excellent tradeoff between video delivery quality and power consumption, and yields significant power saving compared with the conventional equal decoding power allocation （EDPA） approach in wireless video transmission.

关键词： power allocation turbo code data partition joint source and channel code

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Immunodominance and clonal selection inspired multiobjective clustering

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Progress in Natural Science:Materials International 2009年第6期19卷 751-758页

作者： Wenping Ma , Licheng Jiao, Maoguo Gong key laboratory of Intelligent Perception and image Understanding of the Ministry of Education of China, Institute of Intelligent Information processing, Xidian University, Xi’an 710071, China [a]Key Laboratory of Intelligent Perception and Image Understanding of the Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi’an 710071 China

The biological immune system is a highly parallel and distributed adaptive system. The information processing abilities of the immune system provide important insights into the field of computation. Based on immunodominance in the biological immune system and the clonal selection mechanism, a novel data mining method, Immune Dominance Clonal Multiobjective Clustering algorithm (IDCMC), is presented. The algorithm divides an individual population into three sub-populations according to three different measurements, and adopts different evolution and selection strategies for each sub-population. The update of each sub-population, however, is not carried out in isolation. The periodic combination operation of the analysis of the three sub-populations represents considerable advantages in its global search ability. The clustering task is a multiobjective optimization problem, which is more robust with respect to the variety of cluster structures of different datasets than a single-objective clustering algorithm. In addition, the new algorithm can determine the number of clusters automatically, which should identify the most promising clustering solutions in the candidate set. The experimental results, using artificial datasets with different manifold structure and handwritten digit datasets, show that the IDCMC outperforms the PESA-Ⅱ-based clustering method, the genetic algorithm-based clustering technique and the original K-Means algorithm in solving most of the problems tested.

关键词： Artificial immune systems Multiobjective optimization Clustering Unsupervised learning

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Class-specific Artificial Immune Recognition method for Hyperspectral image classification

Class-specific Artificial Immune Recognition method for Hype...

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2012 IEEE 11th International Conference on Signal processing(ICSP 2012)

作者： Qingjie Meng Yanning Zhang Weiwei Yuemei Ren Hongwei She Shaanxi Key Laboratory of Speech and Image Information Processing School of Computer Science Northwestern Polytechnical University

ISBN: (纸本)9781467321969

Artificial immune recognition system (AIRS), as an efficient and successful computational intelligence method, has been widely used for classification. However, this method is seldom used for hyperspectral image classification due to its complexity. To address this problem, a class-specific model based on AIRS, named as Single Class Learning Network AIRS (SCLN-AIRS), is proposed in this paper to improve the classification accuracy for hyperspectral images compared with AIRS based method. For SCLN-AIRS, the outliers of training samples from irrelevant classes are ignored first. Then, a novel MC evolution strategy is proposed to prevent memory cells being affected by other ones from different classes. In the novel model, the calculation complexity is guaranteed by the fact that the class is expressed only by few memory cells while classification result is improved. Experimental results on AVIRIS dataset demonstrate the effectiveness of the proposed method for hyperspectral image classification.

关键词： artificial immune recognition system (AIRS) hyperspectral image superveised classification

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