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	Dynamical stochastic resonance for nonuniform illumination image enhancement 期刊论文 OAI收割 IET Image Processing, 2018, 卷号: 12, 期号: 12, 页码: 2147-2152 作者: Zhang, Yongbin; Liu, Hongjun; Huang, Nan; Wang, Zhaolu \| 收藏 \| 浏览/下载：54/0 \| 提交时间：2018/12/18 Image Enhancement Image Fusion Stochastic Processes Iterative Methods Differential Equations Brightness Dynamical Stochastic Resonance Nonuniform Illumination Image Enhancement Dark Tones Low-contrast Image Enhancement Nonlinear Iteration Monostable Langevin Equation Iteration Parameters Intensity Distribution Visibility Balance Naturalness Balance Illumination Compensation Component Computational Time No-reference Perceptual Quality Assessment Lightness Order Error Low-computational Complexity
	A universal modified LMS algorithm with iteration order hybrid switching 期刊论文 OAI收割 ISA TRANSACTIONS, 2017, 卷号: 67, 页码: 67-75 作者: Cheng, Songsong; Wei, Yiheng; Chen, Yuquan; Liang, Shu; Wang, Yong \| 收藏 \| 浏览/下载：37/0 \| 提交时间：2018/07/30 Fractional order calculus Modified least mean square Response speed Convergence speed Iteration order Switching
	A new algorithm for solving the best-fit sphere of optical aspherical surface (EI CONFERENCE) 会议论文 OAI收割 2nd International Conference on Advances in Materials and Manufacturing, ICAMMP 2011, December 16, 2011 - December 18, 2011, Guilin, China 作者: Lin J.; Lu M. 收藏 \| 浏览/下载：45/0 \| 提交时间：2013/03/25 To solve the best-fit sphere (BFS) accurately is one of the technological keys for the generating and testing of optical aspherical surfaces. This paper presents a new algorithm for solving the BFS of aspherical surfaces to suppress some deficiencies in the existing BFS algorithms. In the proposed approach it is not only suitable for the conic surface a BFS is constructed but also for higher order aspheres. The obtained asphericity and material removal function is more suitable for the machining and test. (2012) Trans Tech Publications which passes through both sides of endpoints in the section o -?xy of the aspherical surfaces Switzerland. the center of the BFS is shifted along the x-axis and its radius of curvature is automatically computed. The variable step size method is proposed to speed up the convergence of the iteration. Through numerically solving the BFS of conic and cubic surface the advantages of the proposed approach are verified. The results show that the proposed approach is of rapid convergence and high accuracy
	Classification of hyperspectral image based on SVM optimized by a new particle swarm optimization (EI CONFERENCE) 会议论文 OAI收割 2012 2nd International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2012, June 1, 2012 - June 3, 2012, Nanjing, China 作者: Gao X.; Yu P.; Yu P. 收藏 \| 浏览/下载：26/0 \| 提交时间：2013/03/25 Support Vector Machine (SVM) is used to classify hyperspectral remote sensing image in this paper. Radial Basis Function (RBF) which is most widely used is chosen as the kernel function of SVM. Selection of kernel function parameter is a pivotal factor which influences the performance of SVM. For this reason Particle Swarm Optimization (PSO) is provided to get a better result. In order to improve the optimization efficiency of kernel function parameter firstly larger steps of grid search method is used to find the appropriate rang of parameter. Since the PSO tends to be trapped into local optimal solutions a weight and mutation particle swam optimization algorithm was proposed in which the weight dynamically changes with a liner rule and the global best particle mutates per iteration to optimize the parameters of RBF-SVM. At last a 220-bands hyperspectral remote sensing image of AVIRIS is taken as an experiment which demonstrates that the method this paper proposed is an effective way to search the SVM parameters and is available in improving the performance of SVM classifiers. 2012 IEEE.
	Multi-focus image fusion algorithm based on adaptive PCNN and wavelet transform (EI CONFERENCE) 会议论文 OAI收割 International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, May 24, 2011 - May 26, 2011, Beijing, China Wu Z.-G.; Wang M.-J.; Han G.-L. 收藏 \| 浏览/下载：84/0 \| 提交时间：2013/03/25 Being an efficient method of information fusion image fusion has been used in many fields such as machine vision medical diagnosis military applications and remote sensing.In this paper Pulse Coupled Neural Network (PCNN) is introduced in this research field for its interesting properties in image processing including segmentation target recognition et al. and a novel algorithm based on PCNN and Wavelet Transform for Multi-focus image fusion is proposed. First the two original images are decomposed by wavelet transform. Then based on the PCNN a fusion rule in the Wavelet domain is given. This algorithm uses the wavelet coefficient in each frequency domain as the linking strength so that its value can be chosen adaptively. Wavelet coefficients map to the range of image gray-scale. The output threshold function attenuates to minimum gray over time. Then all pixels of image get the ignition. So the output of PCNN in each iteration time is ignition wavelet coefficients of threshold strength in different time. At this moment the sequences of ignition of wavelet coefficients represent ignition timing of each neuron. The ignition timing of PCNN in each neuron is mapped to corresponding image gray-scale range which is a picture of ignition timing mapping. Then it can judge the targets in the neuron are obvious features or not obvious. The fusion coefficients are decided by the compare-selection operator with the firing time gradient maps and the fusion image is reconstructed by wavelet inverse transform. Furthermore by this algorithm the threshold adjusting constant is estimated by appointed iteration number. Furthermore In order to sufficient reflect order of the firing time the threshold adjusting constant is estimated by appointed iteration number. So after the iteration achieved each of the wavelet coefficient is activated. In order to verify the effectiveness of proposed rules the experiments upon Multi-focus image are done. Moreover comparative results of evaluating fusion quality are listed. The experimental results show that the method can effectively enhance the edge details and improve the spatial resolution of the image. 2011 SPIE.
	Electromagnetic modeling due to line source in frequency domain using finite element method 期刊论文 OAI收割 CHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITION, 2006, 卷号: 49, 期号: 6, 页码: 1858-1866 作者: Wang Ruo; Wang Miao-Yue; Di Qing-Yun \| 收藏 \| 浏览/下载：38/0 \| 提交时间：2018/09/26 frequency domain line source finite element method forward modeling first order absorption boundary condition compression storage of the coefficient matrix pseudo delta function Gauss-Seidel iteration method
	Electromagnetic modeling due to line source in frequency domain using finite element method 期刊论文 OAI收割 CHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITION, 2006, 卷号: 49, 期号: 6, 页码: 1858-1866 作者: Wang Ruo; Wang Miao-Yue; Di Qing-Yun \| 收藏 \| 浏览/下载：51/0 \| 提交时间：2018/09/26 frequency domain line source finite element method forward modeling first order absorption boundary condition compression storage of the coefficient matrix pseudo delta function Gauss-Seidel iteration method