{"title":"The analysis of equivalent sample of correlated data","authors":"Yan Shi","doi":"10.1109/CISP.2013.6743934","DOIUrl":"https://doi.org/10.1109/CISP.2013.6743934","url":null,"abstract":"We endeavor to obtain the number of equivalent independent samples when the available samples are correlated in radar received system. Comparing the estimated matrix of independent secondary samples with that of correlated secondary samples, in several correlation coefficients, we obtain the equivalent independent number without an information loss.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116091643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yuanyuan Zang, Zhenkuan Pan, J. Duan, Guodong Wang, Weibo Wei
{"title":"A double total variation regularized model of Retinex theory based on nonlocal differential operators","authors":"Yuanyuan Zang, Zhenkuan Pan, J. Duan, Guodong Wang, Weibo Wei","doi":"10.1109/CISP.2013.6743989","DOIUrl":"https://doi.org/10.1109/CISP.2013.6743989","url":null,"abstract":"Image characteristics, such as texture, edge, smoothness, can be much better preserved by using nonlocal differential operators based on patch-distances in image processing. In this paper, we apply with nonlocal differential operators to some existing variation models of Retinex, such as the nonlocal variation model of Retinex (NL_VR); the nonlocal TV regularized model (NL_TV_R) and the nonlocal total variation regularized model with constraints (NL_TV_C). And then we improve and establish a double total variation regularized model of Retinex theory (DTV) and the nonlocal double total regularized model (NL_DTV), which could handles better edges in the illumination. Experiments show that our proposed method and Split Bregman algorithm presented in this paper have higher computational efficiency and accuracy.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"17 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114128054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
W. Pei, J. Wen, Tiantian Xie, Xiangjie Wang, Yong-ying Zhu, Shuxia Liu
{"title":"Rapid identification of oil fingerprints","authors":"W. Pei, J. Wen, Tiantian Xie, Xiangjie Wang, Yong-ying Zhu, Shuxia Liu","doi":"10.1109/CISP.2013.6745256","DOIUrl":"https://doi.org/10.1109/CISP.2013.6745256","url":null,"abstract":"Most marine spills are sudden incidents in harsh marine environment and bring great damage to the marine ecological environment and incalculable harm to the economic development, human health and public safety. The paper studies the extraction of invariant features of oil fingerprints and adaptive multi-scale rapid identification methods to determine the sort and source of the spilled oil quickly. It provides technological support for recovery of the damaged marine ecological environment and development of theoretical system of sudden marine incident. The study can offer scientific basis to defend and reduce marine pollution and protects national marine rights and interests.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124616830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An improved similarity measure in particle filters for robust object tracking","authors":"Xin Wang, Chen Ning, Aiye Shi, Guofang Lv","doi":"10.1109/CISP.2013.6744039","DOIUrl":"https://doi.org/10.1109/CISP.2013.6744039","url":null,"abstract":"Infrared object tracking plays a key role in many research fields, and there is a series of work on applying particle filter to this tracking problem. Most of the PF-based tracking algorithms utilize the Bhattacharyya coefficient as a similarity measure, however, its performance in infrared object tracking is limited due to insufficient discriminative power. In this paper, we present a combined similarity measure under the particle filter framework, which integrates the advantages of the Bhattacharyya coefficient, histogram intersection, and structural similarity. The experimental results are gained by using different infrared image sequences, which show that the proposed measure gives superior discriminative power and achieves more robust and stable tracking performance than the traditional approach.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124731430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A novel MPSK signal classification algorithm based on phase entropy","authors":"Yong-Gang Zhu, Yong-Gui Li, Yi-Yong Zhu","doi":"10.1109/CISP.2013.6743880","DOIUrl":"https://doi.org/10.1109/CISP.2013.6743880","url":null,"abstract":"Automatic modulation classification is very important in cognitive radio and communication reconnaissance systems. Two novel approaches for identifying the modulation format of general M-ary PSK signal are proposed, which are based on the phase entropy. Phase entropy of the first one is estimated in time domain with probability space partitioned into fixed dimensions. And for the second one, the frequency transform is first applied to the phase of the received signal and the entropy of the measured signal is then estimated. Based on a general hypothesis test, the entropies of different modulation signals are compared to classify them. The simulation results illustrate that the proposed algorithm has smaller computational complexity than existing classifier and the second one has better classification performance in low signal-to-noise ratio domain.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129428762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Cluster head election with a fuzzy algorithm for wireless sensor networks","authors":"Zhen Fu","doi":"10.1109/CISP.2013.6743898","DOIUrl":"https://doi.org/10.1109/CISP.2013.6743898","url":null,"abstract":"Focusing on large-scale wireless sensor networks, this paper introduces the idea of fuzzy logic according to the nodes' residual energy, communication range, computing power, neighbor nodes, etc. Using fuzzy comprehensive evaluation method in virtual cluster head selection and the formation of the wireless network hierarchy overcome the randomness of cluster head election in LEACH protocol and uneven distribution of node energy; at the same time, generating the cluster node consequence through network initialization reduces the energy consumption when network constantly selects the cluster head and prolongs the life cycle of wireless sensor network.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123894434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Circle detection using a spiking neural network","authors":"Liuping Huang, Qingxiang Wu, Xiaowei Wang, Zhiqiang Zhuo, Zhenmin Zhang","doi":"10.1109/CISP.2013.6743901","DOIUrl":"https://doi.org/10.1109/CISP.2013.6743901","url":null,"abstract":"The receptive field of neurons plays various roles in biological neural networks. In this paper a spiking neural network model is proposed using a mechanism inspired by the biological receptive field. The network is composed of multiple layers, and the neurons are connected by excitatory and inhibitory synapses. When a visual image presents to the network, location and radius of a circle on the visual image can be obtained from firing rates of the neurons from the corresponding layers. The simulation results show that the network can perform circle detection similar to Hough circle detection and calculations are conducted by a parallel mechanism in a biological manner. This model can be used to explain how a spiking neuron-based network to detect circle, and the high speed parallel mechanism in the model can be used in artificial intelligent systems.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114741319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A PSO-based algorithm for video networks planning optimization","authors":"Jiang Peng, J. Weidong","doi":"10.1109/CISP.2013.6743970","DOIUrl":"https://doi.org/10.1109/CISP.2013.6743970","url":null,"abstract":"In this paper we examine issues of deploying a camera network in a complex environment with obstacles. A camera network is composed of a distributed collection of cameras, each of which has sensing and communicating capabilities. To deploy such camera network, we present a kinetics based particle swarm optimization (PSO) approach. By introducing a kinetics-constraint factor to standard PSO, the fields are covered such that each camera is repelled by both other cameras and obstacles, thereby forcing the network to spread throughout the monitored area. The coverage enhancement is fulfilled by finding an optimal orientation for each camera, guided by PSO optimizer. Experimental results show our method is able to achieve higher coverage rate than conventional methods.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114881105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Long-term trend in non-stationary time series with nonlinear analysis techniques","authors":"L. Deng","doi":"10.1109/CISP.2013.6745231","DOIUrl":"https://doi.org/10.1109/CISP.2013.6745231","url":null,"abstract":"Understanding, modeling, and forecasting the evolution of complex dynamic system is an important but hard task in many natural phenomena. In the present paper, three advanced analysis approaches, including the rescaled range analysis, empirical mode decomposition and cross-recurrence plot, have been proposed to analyze the long-term persistence and secular trend of nonlinear and non-stationary time series. The case study uses the chaotic time-series data of solar-activity indicators in the time interval from 1874 May to 2013 March. The analysis results indicate that the combination of these three techniques is an effective tool not only for capturing the long-range persistence of non-stationary processes, but also for determining the secular trend of a complex time-series.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124021646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Pixel level image fusion based the wavelet transform","authors":"Mingjing Li, Y. Dong, Xiaoli Wang","doi":"10.1109/CISP.2013.6745310","DOIUrl":"https://doi.org/10.1109/CISP.2013.6745310","url":null,"abstract":"Image fusion algorithm based on wavelet transform was proposed in this paper to improve quality of image and meet the needs of applications of vision. Because of the high frequency component and low frequency component representing different information of an image, two or more images to be fused should be firstly decomposed into sub-images with different frequency. Then, the different rules of fusion were used to fuse sub-images on different frequency under the certain rules, and finally these sub-images are fused to reconstruct image with plentiful information. Experimental results by MATLAB show that image fusion based on wavelet adds more details and achieves a good fusion results, and the fusion effects would be better if decomposition layer change to more.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124039747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}