Key Laboratory of Optical Fiber Communication Technology

Chongqing, China

Key Laboratory of Optical Fiber Communication Technology

Chongqing, China
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Chen Y.,Chongqing University of Posts and Telecommunications | Zhang Y.-L.,Chongqing University of Posts and Telecommunications | Liu H.-L.,Key Laboratory of Optical Fiber Communication Technology | Yang K.,Chongqing University of Posts and Telecommunications
Guangdianzi Jiguang/Journal of Optoelectronics Laser | Year: 2016

Aiming at that it is difficult to solve the 1/f noise removing and the loss of signal for fiber Bragg gratting (FBG) sensing signal, the compressed sensing (CS) is used to process the sensing signal in this paper. But CS takes the sparsity as priori condition. The sparsity is determined with innovation method proposed in this paper, a new algorithm which is called group twice orthogonal matching pursuit (GtOMP) based on twice orthogonal matching pursuit (TOMP) and group orthogonal matching pursuit (GOMP) is proposed, and the number of atoms in each iteration as well as the number of iteration is obtained. First of all, the calculated and normalized correlation coefficients in descending order used with the method of saturation value to determine the sparsity. And the number of atoms each iteration is confirmed by using smoothness. In the end, the proposed method is applied to reconstruct the FBG signal. Simulatin results show that, compared with the similar TOMP algorithm, the algorithm in this paper not only reduces the running time, but also decreases the reconstruction error of 6~20%, and compared with other algorithms, signal noise ratio (SNR) of the signal after processing by the proposed method can be improved by more than 27 dB. © 2016, Science Press in China. All right reserved.


Chen Y.,Chongqing University of Posts and Telecommunications | Xiong J.,Chongqing University of Posts and Telecommunications | Liu H.-L.,Key Laboratory of Optical Fiber Communication Technology | Fan Q.,Chongqing University of Posts and Telecommunications
Telkomnika (Telecommunication Computing Electronics and Control) | Year: 2014

For getting the useful object information from infrared image and mining more detail of low light level (LLL) image, we propose a new fusion method based on segmentation and enhancement methods in the paper. First, using 2D maximum entropy method to segment the original infrared image for extracting infrared target, enhancing original LLL image by Zadeh transform for mining more detail information, on the basis of the segmented map to fuse the enhanced LLL image and original infrared image. Then, original infrared image, the enhanced LLL image and the first fused image are used to realize fusion in nonsubsampled contourlet transform (NSCT) domain, we get the second fused image. By contrast of experiments, the fused image of the second fused method's visual effect is better than other methods' from the literature. Finally, Objective evaluation is used to evaluate the fused images' quality, its results also show that the proposed method can pop target information, improve fused image's resolution and contrast.


Chen Y.,Chongqing University of Posts and Telecommunications | Xiao W.-Z.,Chongqing University of Posts and Telecommunications | Liu H.-L.,Key Laboratory of Optical Fiber Communication Technology | Sun L.-Z.,Chongqing University of Posts and Telecommunications
Telkomnika | Year: 2013

Locating content in unstructured peer-to-peer networks is a challenging problem. This paper presents a novel semantic small world resource search mechanism to address the problem. By using vector space model to compute the semantic relevance and applying small world properties such as low average hop distance and high clustering coefficient to construct a cluster overlay. In semantic small world system, the search mechanism is divided into two parts, searching at cluster and outside cluster through inner link and short link, so that it can achieve the incremental research. It significantly reduces the average path length and query cost. Meanwhile, the simulation results show that semantic small world scheme outperforms K-random walks and flooding scheme than higher query hit rate and lower query latency.


Chen Y.,Chongqing University of Posts and Telecommunications | Sun L.-Z.,Chongqing University of Posts and Telecommunications | Liu H.-L.,Key Laboratory of Optical Fiber Communication Technology | Xiao W.-Z.,Chongqing University of Posts and Telecommunications
Telkomnika | Year: 2013

Chord protocol is one of the most classical protocols in structured P2P system, with the good effect, reliability, high query efficiency, and many other advantages. However, Chord agreement remains two main shortcomings the one that the searching speed of resources is slower, and the other that the detention of routing is higher. This paper in view of these shortcomings, combination with modification, then put forward the new Chord structure that super nodes and common nodes coexist, super nodes management general nodes. The new structure using Zipf-law determines the proportion of super nodes and ordinary nodes. The last, the new structure is simulated by simulation software, and the improved Chord protocol make better the previous shortcoming through the new structure compares with the Chord protocol.


Chen Y.,Chongqing University of Posts and Telecommunications | He M.,Chongqing University of Posts and Telecommunications | Chen L.,Chongqing University of Posts and Telecommunications | Liu H.,Key Laboratory of Optical Fiber Communication Technology | Liu H.,Chongqing University
Hongwai yu Jiguang Gongcheng/Infrared and Laser Engineering | Year: 2013

Demodulation system is the core sensing technology of optical fiber Bragg grating (FBG). De-noising and seeking the peak wavelength are the two important factors that influence the demodulation accuracy. In order to obtain the precise wavelength drift, aiming at the defects of the traditional demodulation methods, a new wavelength detection scheme for optical fiber Bragg grating (FBG) was put forward, which was composed of an improved de-noising method and the Gaussian fitting peak searching algorithm. The translation invariant wavelet combined with the new threshold value and the proposed new threshold function method to deal with noisy FBG sensor signal; then the Gaussian fitting peak searching algorithm was adopted to find the peak wavelength of the de-noised signal for further analysis. The experiment result shows that the improved invariant wavelet can deal with noisy FBG sensor signal with different SNR and get a higher SNR value and a lower mean square error value than the other wavelet de-noising methods mentioned; this kind of wavelength detection technique can get the measurement maximum peak error of less than 1 pm, which means a much higher accuracy than general wavelength detection methods.


Chen Y.,Chongqing University of Posts and Telecommunications | Xiong J.,Chongqing University of Posts and Telecommunications | Liu H.-L.,Key Laboratory of Optical Fiber Communication Technology | Fan Q.,Chongqing University of Posts and Telecommunications
Optik | Year: 2014

On fusing infrared and visible image, the traditional fusion method cannot get the better image quality. Based on neighborhood characteristic and regionalization in NSCT (Nonsubsampled Contourlet Transform) domain, the fusion algorithm was proposed. Firstly, NSCT was adopted to decompose infrared and visible images at different scales and directions for the low and high frequency coefficients, the low frequency coefficients which were fused with improving regional weighted fusion method based on neighborhood energy, and the high-frequency coefficients were fused with multi-judgment rule based on neighborhood characteristic regional process. Finally, the coefficients were reconstructed to obtain the fused image. The experimental results show that, compared with the other three related methods, the proposed method can get the biggest value of IE (information entropy), MI(VI,F) (mutual information from visible image), MI(VI,F) (mutual information from infrared image), MI (sum of mutual information), and QAB/F (edge retention). The proposed method can leave enough information in the original images and its details, and the fused images have better visual effects. © 2014 Elsevier GmbH.


Chen Y.,Chongqing University of Posts and Telecommunications | Wang K.,Chongqing University of Posts and Telecommunications | Liu H.-L.,Key Laboratory of Optical Fiber Communication Technology | Chen L.-J.,Chongqing University of Posts and Telecommunications | Yang X.,Chongqing University of Posts and Telecommunications
Optik | Year: 2014

In order to gain the wavelength drift of Mach-Zehnder interferometer (MZI) sensor system, achieve the measurement of ambient environment parameters precisely, so, need to treatment optical fiber sensing signal with noise. Firstly, introduce the method of neighborhood wavelet coefficient by analyzing the drawback of traditional wavelet de-noising methods. Secondly, an improved threshold is putted forward based on neighboring coefficients in this paper which is to overcome the shortcomings of traditional wavelet methods. Finally, the threshold function proposed by this paper deal with MZI sensing noisy signal together with improved threshold. The simulation result shows that the new method can get the better signal-to-noise ratios (SNR) and root of mean square error (MSE) simultaneously and gain the reconstruction signal of the higher correlation coefficient (CC). Compared with the soft and hard threshold method, its SNR increases by 2-4 db, and compared with NeighCoeff, its SNR improves by 1.2 db. The peak error is 1.6 pm. So, the system can meet the requirement of improving sensor detection precision. © 2013 Elsevier GmbH.


Chen Y.,Chongqing University of Posts and Telecommunications | Chen L.-J.,Chongqing University of Posts and Telecommunications | Liu H.-L.,Key Laboratory of Optical Fiber Communication Technology | Wang K.,Chongqing University of Posts and Telecommunications
Optik | Year: 2013

A new Fiber Bragg Grating (FBG) wavelength demodulation scheme is studied in the paper, which consists of an improved de-noising method and Gaussian fitting peak searching algorithm. The improved translational invariant wavelet without threshold adjust factor is proposed to get a better de-noising performance for FBG sensor signal and overcome the drawbacks of soft or hard threshold wavelets. In order to get a high wavelength demodulation precision of FBG sensor signal, this de-noising method is designed to combine with Gaussian fitting peak searching algorithm. The simulation results show that the wavelength maximum measurement error is lower than 1 pm, and can get a much higher accuracy. © 2013 Elsevier GmbH.


Chen Y.,Chongqing University of Posts and Telecommunications | Xu M.,Chongqing University of Posts and Telecommunications | Liu H.-L.,Key Laboratory of Optical Fiber Communication Technology | Huang W.-N.,Chongqing University of Posts and Telecommunications | Xing J.,Chongqing University of Posts and Telecommunications
Optik | Year: 2014

To gain the wide view angle and high resolution image stitched by the sequence images overlapped in the same scene, this paper proposes a new image mosaic method of combining the improved SIFT algorithm with Canny feature edge detection based on the traditional scale invariant feature transform (SIFT) algorithm. First, we extract feature points of the image with the SIFT algorithm. Then, we construct an improved 18-dimensional feature descriptor consisting of 12 gradient values in a circular window, three cumulative gray-scale values and three gray-scale differences in a concentric circular window. Second, this method preserves the features in 16-neighborhood of the Canny edge image. Then, the extracted feature points search for the coarse matching points through the BBF, and the coarse matching points are purified with the random consistency (RANSAC) algorithm, which calculates the transformational matrix H among the images with these purified feature points. Finally, the seamless mosaic of images is completed with the image fusion algorithm of slipping in and out. In the experiment, we process the aerial image and the images that had changed in terms of translation, rotation and zoom, and parallax with the traditional SIFT and the proposed method, respectively. The results indicate that mosaic time, respectively reduced by 11.8%, 13.5%, 7.7% and 21.6%, the root mean squared error, respectively reduced by 80.1%, 0.002%, 4.4% and 58.1% through the proposed method in this paper, compared with the SIFT. Even for an image subjected to such situations as illumination, rotation, scaling and affine distortion, the matching performance can be improved with the proposed method. © 2014 Elsevier GmbH.

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