中国科学院机构知识库网格系统: 检索

The Optimal Precursors for ENSO Events Depicted Using the Gradientdefinition-based Method in an Intermediate Coupled Model CNKI期刊论文 OAI收割
2019
作者: Bin MU; Juhui REN; Shijin YUAN

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收藏 | 浏览/下载：2/0 | 提交时间：2024/12/18

optimal precursor ENSO gradient-definition-based method conditional nonlinear optimal perturbation intermediate coupled model

Compressive sensing for noisy solder joint imagery based on convex optimization 期刊论文 OAI收割
SOLDERING & SURFACE MOUNT TECHNOLOGY, 2016, 卷号: 28, 期号: 2, 页码: 114-122
作者: Zhao, Huihuang; Chen, Jianzhen; Xu, Shibiao; Wang, Ying; Qiao, Zhijun

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收藏 | 浏览/下载：31/0 | 提交时间：2016/10/20

Noisy Solder Joint Imagery Compressive Sensing (Cs) Convex Optimization Gradient-based Method Orthogonal Matching Pursuit Greedy Basis Pursuit Subspace Pursuit And Compressive Sampling Matching Pursuit Iterative Re-weighted Least Squares

Features extraction and matching of teeth image based on the SIFT algorithm (EI CONFERENCE) 会议论文 OAI收割
2012 2nd International Conference on Computer Application and System Modeling, ICCASM 2012, July 27, 2012 - July 29, 2012, Shenyang, China
作者: Wang X.; Wang X.; Wang X.

收藏 | 浏览/下载：28/0 | 提交时间：2013/03/25

Using of SIFT algorithm in the image of teeth model can detect the features of the teeth image effectively. In this approach first search over all scales and image locations by using a difference-of-Gaussian function to identify potential interest points that are invariant to scale and orientation. Second select keypoints based on measures of their stability and a detailed model is fit to determine location and scale at each candidate location. Third assign one or more orientations to each keypoint location based on local image gradient directions. Last measure the local image gradients at the selected scale in the region around each keypoint. And then use the KNN algorithm to match the features. Through lots of experiments and comparing with other feature extraction methods this method can detect the features of the teeth model effectively and offer some available parameters for 3D reconstruction of the teeth model. the authors.

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：72/0 | 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.

MGRG-morphological gradient based 3D region growing algorithm for airway tree segmentation in image guided intervention therapy (EI CONFERENCE) 会议论文 OAI收割
2nd International Symposium on Bioelectronics and Bioinformatics, ISBB 2011, November 3, 2011 - November 5, 2011, Suzhou, China
作者: Zhang T.; Gao X.

收藏 | 浏览/下载：44/0 | 提交时间：2013/03/25

Accurate surgical planning and guidance plays an important role in successful implementation of image guided intervention. In interventional lung cancer diagnosis and treatments precise segmentation of airway trees from lung CT images provides crucial visualization for preoperative planning and intraoperative guidance to avoid major trachea injury. While 3D region growing can segment main the parts of an airway tree (trachea left and right main bronchus as well as bronchi) the method fails at bronchiole segmentation and is not robust. Mathematical morphology is an anatomical detective. In this paper we propose a morphological gradient based region growing (MGRG) algorithm to overcome the intensity inhomogeneity and improve the robustness of 3D region growing on extraction of bronchioles. The MGRG algorithm is validated using lung CT images and results show that it is able to segment bronchioles and outperforms the traditional region growing method on airway tree segmentation. 2011 IEEE.

An adaptive edge detection method based on Canny operator (EI CONFERENCE) 会议论文 OAI收割
2011 International Conference on Civil Engineering and Building Materials, CEBM 2011, July 29, 2011 - July 31, 2011, Kunming, China
作者: Chen Y.

收藏 | 浏览/下载：39/0 | 提交时间：2013/03/25

This paper proposes an adaptive Canny operator edge detection algorithm. The proposed method can automatically set the threshold value according to the different image gray-scale gradient histogram adaptively and improve the performance in the detail edge detection and good localization. Experiments show that this method produces better edge detection results performance than the Otsu method. Besides our method Roberts operator Prewitt operator Sobel operator Log operator and Canny operator based on Otsu algorithm are also tested for comparisons. (2011) Trans Tech Publications Switzerland.

Realization of the imaging-auto-focus on the APRC using splicing- CCD (EI CONFERENCE) 会议论文 OAI收割
International Conference on Graphic and Image Processing, ICGIP 2011, October 1, 2011 - October 2, 2011, Cairo, Egypt
Lu Z.; Guo Y.; Xue X.; Ma T.; Lv H.

收藏 | 浏览/下载：13/0 | 提交时间：2013/03/25

It is difficult to deal with the auto-focus of aerial push-broom remote sensing camera (APRC) based on image processing. First of all this paper recommended the Splicing structure of CCD in the APRC Based on this auto-focus method which is made use of the overlapping area of CCD mosaic structure was proposed combined with the characteristic of the imaging mode. After analyzing of experiments about all kinds of focus-examine functions based on image processing the gradient square function has been chosen. The experimental results show that the proposed auto-focus method for the APRC is proved to be feasible and real-time. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

A parallel decomposition algorithm for training multiclass kernel-based vector machines 期刊论文 OAI收割
OPTIMIZATION METHODS & SOFTWARE, 2011, 卷号: 26, 期号: 3, 页码: 431-454
作者: Niu, Lingfeng; Yuan, Ya-Xiang

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收藏 | 浏览/下载：20/0 | 提交时间：2018/07/30

Kernel-based vector machines decomposition method projected gradient parallel algorithm

Driving and image enhancement for CCD sensing image system (EI CONFERENCE) 会议论文 OAI收割
2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010, July 9, 2010 - July 11, 2010, Chengdu, China
Zhang M.; Ren J.

收藏 | 浏览/下载：27/0 | 提交时间：2013/03/25

The paper designs a driving circuit of high sensitive wide dynamic for CCD sensing imaging system which adopts a Dalsa-made high resolution full-frame 33-mega pixels area CCD FTF5066M. Field Programmable Gate Array (FPGA) is used as the main device to accomplish the timing design of the circuits and power driver control of the sensor. By using the Correlated Double Sampling (CDS) technique the video noise is reduced and the SNR of the system is increased. The output rate of the imaging system designed with integrated chip can reach to 1.3 frames per second through bi-channel output. We use the histogram specification to adjust the brightness of the captured image. And then use the median filtering to suppress the noise. The traditional gray mean gradient (GMG) and the objective evaluation method based on Human Visual System (HVS) used to verify the effect of image enhancement. 2010 IEEE.

Self-adaptive threshold canny operator in color image edge detection (EI CONFERENCE) 会议论文 OAI收割
2009 2nd International Congress on Image and Signal Processing, CISP'09, October 17, 2009 - October 19, 2009, Tianjin, China
Luo T.; Zheng X.-F.; Ding T.-F.

收藏 | 浏览/下载：16/0 | 提交时间：2013/03/25

It needs to set the two thresholds of classical Canny Operator manually which confined this algorithm. A lot of research on adaptive thresholds choice method has been done to conquer this shortcoming. Based on the gradient histogram which is studied constantly in the past a method of gradient histogram difference diagram with adaptive image classification techniques is proposed in this paper. It automatically sets the two thresholds and avoids disconnected or false edges in detection. Experiments prove that the method is threshold-adaptive and the edge detection performs well in color image whose larger gradient amplitude pixels are mainly located in the edges between the target and background. 2009 IEEE.