中国科学院机构知识库网格系统: 检索

Forecasting container throughput of Qingdao port with a hybrid model 期刊论文 OAI收割
JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY, 2015, 卷号: 28, 期号: 1, 页码: 105-121
作者: Huang Anqiang; Lai Kinkeung; Li Yinhua; Wang Shouyang

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收藏 | 浏览/下载：11/0 | 提交时间：2021/01/14

PROJECTION PURSUIT REGRESSION WAVELET-BASED DETECTION FINANCIAL TIME-SERIES OUTLIER DETECTION GENETIC ALGORITHMS NOVELTY DETECTION NEURAL-NETWORKS PREDICTION Container throughput forecast genetic programming algorithm outlier processing projection pursuit regression

An auto-focus algorithm of fast search based on combining rough and fine adjustment (EI CONFERENCE) 会议论文 OAI收割
3rd international Conference on Manufacturing Science and Engineering, ICMSE 2012, March 27, 2012 - March 29, 2012, Xiamen, China
作者: Zhang S.; Zhang Y.

收藏 | 浏览/下载：28/0 | 提交时间：2013/03/25

A coarse and fine combined fast search and auto-focusing algorithm was suggested in this paper. This method can automatically search and find the focal plane by evaluating the image definition. The Krisch operator based edge energy function was used as the big-step coarse focusing and then the wavelet transform based image definition evaluation function which is sensitivity to the variation in image definition was used to realize the small-step fine focusing in a narrow range. The un-uniform sampling function of the focusing area selection used in this method greatly reduces the workload and the required time for the data processing. The experimental results indicate that this algorithm can satisfy the requirement of the optical measure equipment for the image focusing. (2012) Trans Tech Publications.

Study on time registration method for photoelectric theodolite data fusion (EI CONFERENCE) 会议论文 OAI收割
10th World Congress on Intelligent Control and Automation, WCICA 2012, July 6, 2012 - July 8, 2012, Beijing, China
Yang H.-T.; Gao H.-B.

收藏 | 浏览/下载：18/0 | 提交时间：2013/03/25

In range measurement theodolite and radar constitute a real-time tracking system at different sites to track the same target in the air and get useful information exactly and timely. As the optical theodolite and radar have different sampling frequency and measurement system the data is sent to the fusion center is asynchronous. This paper proposed a time registration method based on multi-sensor data using Wavelet neural network algorithm which not only better solved the basic problems of theodolite fusion tracking but also improve the efficiency of data fusion. Simulation experiment and comparison with other time registration method have shown the advantage of this method. 2012 IEEE.

The Application of Wavelet-Based Contourlet Transform on Compressed Sensing 会议论文 OAI收割
2012 International Conference on Multimedia and Signal Processing, Shanghai, China, December 7-9, 2012
作者: Du M(杜梅); Zhao HC(赵怀慈); Zhao CY(赵春阳)

收藏 | 浏览/下载：91/0 | 提交时间：2012/12/28

Sparse Representation Wavelet-Based Contourlet Transform Block Compressed Sensing Iterative Hard Thresholding Algorithm

Multi-scale decomposition of point process data SCI/SSCI论文 OAI收割
2012
作者: Ma T.; Pei T.

收藏 | 浏览/下载：46/0 | 提交时间：2014/12/24

Density based clustering method Homogeneous point process Wavelet transform MCMC EM kth nearest distance nearest-neighbor method delaunay triangulation density-estimation genetic algorithm spatial-patterns cluster-analysis model features inference space

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：78/0 | 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.

Image compression based on contourlet and no lists SPIHT (EI CONFERENCE) 会议论文 OAI收割
2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, CMCE 2010, August 24, 2010 - August 26, 2010, Changchun, China
作者: Zhang S.

收藏 | 浏览/下载：47/0 | 提交时间：2013/03/25

The volume of raw image data captured by the high resolution camera is extremely huge. Thus the efficient image compression method should be used to decrease the bit rate. The image compression method based on wavelet is used more widely nowadays. However two dimensional wavelet is only the tensor product of the one dimensional wavelet whose support region of basis function is extended from interval to square. Contourlet is an image multiscale geometric analysis tool which could represent image sparsely and has strong capability of nonlinear approximation. The basis function of contourlet is multidirectional and anisotropic. Nevertheless contourlet is redundant. So the non-redundant Wavelet Based Contourlet Transform (WBCT) is used in this paper. The SPIHT algorithm is very efficient way to coding the significant coefficients. And the improved no lists SPIHT is more easy to implemented by hardware. Image compression method based on the combination of both wavelet based contourlet transform and no lists SPIHT coding is proposed in the paper. Experiment shows that compared to wavelet based scheme the contourlet scheme can reserve the texture of the image. For barbara test image when coding at low bit rate the PSNR can improve about 0.2dB. 2010 IEEE.

Destriping method using lifting wavelet transform of remote sensing image (EI CONFERENCE) 会议论文 OAI收割
2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, CMCE 2010, August 24, 2010 - August 26, 2010, Changchun, China
作者: He B.

收藏 | 浏览/下载：30/0 | 提交时间：2013/03/25

Based on the characteristic of striping noise in remote sensing images a new destriping noise technique for the improved multi-threshold method using lifting wavelet transform applied to remote sensing imagery is presented in this letter. Have used the lifting wavelet decomposition algorithm the thresholds are determined by corresponding wavelet coefficients in every scale. Remote sensing imagery is so large that the algorithm must be fast and effective. The lifting wavelet transform is easily realized and inexpensive in computer time and storage space compared with the traditional wavelet transform. We also compare the method with some traditional destriping methods both by visual inspection and by appropriate indexes of quality of the denoised images. From the comparison we can see that the adaptive threshold method can preserve the spectral characteristic of the images while effectively remove striping noise and it did better than the existed ones. 2010 IEEE.

A new image fusion algorithm based on wavelet transform (EI CONFERENCE) 会议论文 OAI收割
2010 3rd International Conference on Advanced Computer Theory and Engineering, ICACTE 2010, August 20, 2010 - August 22, 2010, Chengdu, China
作者: He X.; Zhang Y.; Zhang L.-G.; Zhang L.-G.

收藏 | 浏览/下载：13/0 | 提交时间：2013/03/25

A new image fusion algorithm based on lifting wavelet transform is presented in this paper. The source images are decomposed using lifting wavelet transform respectively. Aiming at the coefficients of low frequency and high frequency this algorithm choose a different rule to fuse the image. To the low frequency the spatial frequency based on the neighborhood add consistency check is elected as the fusion guide. And the absolute maximum based on detail coefficients is selected as the guide to the high frequency. After that the fused image is obtained by using inverse lifting wavelet transform. Taking the ratio space frequency error and the mean gradient as criterions experimental results demonstrate that the algorithm is very effective. 2010 IEEE.

Real-time matching algorithm of navigation image based on corner detection (EI CONFERENCE) 会议论文 OAI收割
International Symposium on Photoelectronic Detection and Imaging 2009: Advances in Imaging Detectors and Applications, June 17, 2009 - June 19, 2009, Beijing, China
作者: Zhang T.

收藏 | 浏览/下载：46/0 | 提交时间：2013/03/25

In order to meet requirement of real-time and high accuracy in image matching aided navigation SSDA algorithm is used to match remote sensing image and template image coarsely a fast and effective algorithm of remote sensing image matching based on corner detection is put forward. With the combination of rough and fine match when the matching result is bigger than one to count absolute value sum of energy difference of characteristic point energy to realize fine match of remote sensing image and template image to locate the position of template image in remote sensing image accurately. Simulation experiment proves that the matching of a remote sensing image resolution of 1018*1530 and a template image resolution of 150*90 can be fulfilled within 2.392 second wavelet transform is used to acquire low frequency component to realize image compression to decrease calculation work and increase matching speed. Harris corner detection algorithm is used to detect corner of remote sensing image and template image and energy of every corner is calculated the algorithm is robust and effective real time image navigation can be achieved. 2009 SPIE.