[1]
|
He You, Wang Guo-Hong, Guan Xin. Information Fusion Theory With Applications. Beijing: Electronic Industry Press, 2010(何友, 王国宏, 关欣. 信息融合理论及应用. 北京: 电子工业出版社, 2010)
|
[2]
|
[2] Simonea G, Farinab A, Morabitoa F C, Serpicoc S B, Bruzzoned L. Image fusion techniques for remote sensing applications. Information Fusion, 2002, 3(1): 3-15
|
[3]
|
[3] Ashraf S, Brabyn L, Hicks B J. Image data fusion for the remote sensing of freshwater environments. Applied Geography, 2012, 32(2): 619-628
|
[4]
|
[4] Du P J, Chen Y, Xia J S, Tan K. A novel remote sensing image classification scheme based on data fusion, multiple features and ensemble learning. Journal of the Indian Society of Remote Sensing, 2013, 42(2): 213-222
|
[5]
|
[5] Huang B, Zhang H K, Song H H, Wang J, Song C Q. Unified fusion of remote-sensing imagery: generating simultaneously high-resolution synthetic spatial-temporal-spectral earth observations. Remote Sensing Letters, 2013, 4(6): 561-569
|
[6]
|
[6] Du P J, Liu S C, Xia J S, Zhao Y D. Information fusion techniques for change detection from multi-temporal remote sensing images. Information Fusion, 2013, 14(1): 19-27
|
[7]
|
Luo Bin, Wang Yong-Tian, Liu Yue. Multi-sensor data fusion for optical tracking of head pose. Acta Automatica Sinica, 2013, 36(9): 1239-1249 (罗斌, 王涌天, 刘越. 光学头部姿态跟踪的多传感器数据融合研究. 自动化学报, 2013, 36(9): 1239-1249)
|
[8]
|
Han Chong-Zhao, Zhu Hong-Yan, Duan Zhan-Sheng. Multi-Source Information Fusion (2nd Edition). Beijing: Tsinghua University Press, 2010(韩崇昭, 朱红艳, 段战胜. 多源信息融合. 第2版. 北京: 清华大学出版社, 2010)
|
[9]
|
[9] Hall D L, Llinas J. Handbook of Multisensor Data Fusion. New York: CRC Press, 2001
|
[10]
|
Llinas J, Bowman C, Rogova G, Steinberg A, Waltz E, White F E. Revisiting the JDL data fusion model II(C). In: Proceedings of the 2004 International Conference on Information Fusion. Stockholm, Sweden, 2004. 1218-1230
|
[11]
|
Mitchell H B. Data Fusion: Concepts and Ideas. Berlin and Heidelberg: Springer-Verlag, 2012
|
[12]
|
Dasarathy B V. Decision Fusion. Los Alamitos, CA: IEEE Computer Society Press, 1994
|
[13]
|
Solano M A, Ekwaro-Osire S, Tanik M M. High-level fusion for intelligence applications using recombinant cognition synthesis. Information Fusion, 2012, 13(1): 79-98
|
[14]
|
Quaranta C, Balzarotti G. Technique for radar and infrared search and track data fusion. Optical Engineering, 2013, 52(4): 046401
|
[15]
|
Amarsaikhan D, Saandar M, Ganzorig M, Blotevogel H H, Egshiglen E, Gantuyal R, Nergui B, Enkhjargal D. Comparison of multisource image fusion methods and land cover classification. International Journal of Remote Sensing, 2011, 38(8): 2532-2552
|
[16]
|
Lei Lin. Ship Feature Extraction and Fusion in Multiple Remote Sensing Images [Ph.D. dissertation], National University of Defense Technology, China, 2008 (雷琳. 多源遥感图像舰船目标特征提取与融合技术研究 [博士学位论文], 国防科学技术大学, 中国, 2008)
|
[17]
|
Zhao Shu-He. Decision Level Fusion of Multiple Remote Sensing Images and Its Application [Ph.D. dissertation], Nanjing University, China, 2003 (赵书河. 多源遥感影像决策级融合及其应用研究 [博士学位论文], 南京大学, 中国, 2003)
|
[18]
|
McCullough C L, Dasarathy B V, Lindberg P C. Multi-level sensor fusion for improved target discrimination. In: Proceedings of the 35th Conference on Decision and Control. Kobe, Japan: IEEE, 1996. 3674-3675
|
[19]
|
Hussain M S, Calvo R A, Pour P A. Hybrid fusion approach for detecting affects from multichannel physiology. Affective Computing and Intelligent Interaction Lecture Notes in Computer Science, 2011, 6974: 568-577
|
[20]
|
Deng Xiao-Ling, Ni Jiang-Qun, Li Zhen, Dai Fen. Foreground extraction from low depth-of-field images based on colour-texture and HOS features. Acta Automatica Sinica, 2013, 39(6): 846-851 (邓小玲, 倪江群, 李震, 代芬. 多特征融合的低景深图像前景提取算法. 自动化学报, 2013, 39(6): 846-851)
|
[21]
|
Hou Shu-Dong, Sun Quan-Sen. Sparsity preserving canonical correlation analysis with application in feature fusion. Acta Automatica Sinica, 2012, 38(4): 659-665 (候书东, 孙权森. 稀疏保持典型相关分析及在特征融合中的应用. 自动化学报, 2012, 38(4): 659-665)
|
[22]
|
Wang Da-Wei. Research on Target Recognition Based on Feature-Level Image Fusion [Ph.D. dissertation], Chinese Academy of Sciences, China, 2010 (王大伟. 基于特征级图像融合的目标识别技术研究 [博士学位论文], 中国科学院研究生院, 中国, 2010)
|
[23]
|
Yang Jian, Yang Jing-Yu, Gao Jian-Zhen. Handwritten character recognition based on parallel feature combination and generalized K-L expansion. Journal of Software, 2003, 14(3): 490-495(杨建, 杨静宇, 高建贞. 基于并行特征组合与广义K-L变换的字符识别. 软件学报, 2003, 14(3): 490-495)
|
[24]
|
Lang Fang-Nian, Zhou Ji-Liu, Zhong Fan, Yan Bin. Quaternion based image information parallel fusion. Acta Automatica Sinica, 2013, 33(11): 1136-1143 (朗方年, 周激流, 钟钒, 闫斌. 基于四元数的图像信息并行融合. 自动化学报, 2007, 33(11): 1136-1143)
|
[25]
|
Bebis G, Gyaourova A, Singh S, Pavlidis I. Face recognition by fusing thermal infrared and visible iamgery. Image and Vision Computing, 2006 24(7): 727-742
|
[26]
|
Qin Zheng, Bao Fu-Min, Li Ai-Guo. Digital Image Fusion. Xi'an: Xi'an Jiaotong University Press, 2004(覃征, 鲍褔民, 李爱国. 数字图像融合. 西安: 西安交通大学出版社, 2004)
|
[27]
|
Sengupta N, Sil J. Evaluation of rough set theory based network traffic data classifier using different discretization method. International Journal of Information and Electronics Engineering, 2012, 2(3): 338-341
|
[28]
|
Shang C J, Barnes D. Fuzzy-rough feature selection aided support vector machines for Mars image classification. Computer Vision and Image Understanding, 2013, 117(3): 202-213
|
[29]
|
Jensen R, Shen Q. New approaches to fuzzy-rough feature selection. IEEE Transactions on Fuzzy Systems, 2009, 17(4): 824-838
|
[30]
|
Alex M, Vasilescu O, Terzopoulos D. A tensor approach to image sysnthesis, analysis and recognition. In: Proceedings of the 6th International Conference on 3-D Digital Imaging and Modeling. Montreal, QC: IEEE, 2007. 3-12
|
[31]
|
Hu Liang-Mei. Information Fusion-based for Image Understanding [Ph.D. dissertation], Hefei University of Technology, China, 2006(胡良梅. 基于信息融合的图像理解方法研究 [博士学位论文], 合肥工业大学, 中国, 2006)
|
[32]
|
Li Xin-De. Research on Fusion Method of Imperfect Information from Multi-source and Its Application [Ph.D. dissertation], Huazhong University of Science and Technology, China, 2007 (李新德. 多源不完善信息融合方法及其应用研究 [博士学位论文], 华中科技大学, 中国, 2007)
|
[33]
|
Klein L A. Sensor and Data Fusion Concepts and Applications. Bellingham, WA: SPIE Optical Engineering Press, 1999
|
[34]
|
Li Q Q, Tao J B, Hu Q W, Liu P C. Decision fusion of very high resolution images for urban land-cover mapping based on Bayesian network. Journal of Applied Remote Sensing, 2013, 7(1): 073551
|
[35]
|
Wu H D, Siegel M, Stiefelhagen R, Yang L. Sensor fusion using dempster-shafer theory. In: Proceedings of the 19th IEEE Conference on Instrumentation and Measurement Technology. Anchorage, AK: IEEE, 2002. 7-12
|
[36]
|
Sun S Y, Gao J, Chen M F, Xu B G, Ding Z G. FS-DS based multi-sensor data fusion. Journal of Software, 2013, 8(5): 1157-1161
|
[37]
|
Fontani M, Bianchi T, De Rosa A, Piva A, Barni M. A framework for decision fusion in image forensics based on Dempster-Shafer theory of evidence. IEEE Transactions on Information Forensics and Security, 2013, 8(4): 593-607
|
[38]
|
Dezert J. Foundations for a new theory of plausible and paradoxical reasoning. Information and Security, 2002, 9: 90-95
|
[39]
|
Elhassouny A, Idbraim S, Bekkarri A, Mammass D, Ducrot D. Multisource fusion/classification using ICM and DSmT with new decision rule. In: Proceedings of the 5th International Conference on Image and Signal Processing (ICISP, 2012). Berlin Heidelberg: Springer, 2012. 56-64
|
[40]
|
Ding Sheng-Feng. Research on Multi-source Image Fusion Based on Fuzzy Reference [Master dissertation], Nanjing University of Science and Technology, China, 2004 (丁胜峰. 基于模糊推理的多源图像融合研究 [硕士学位论文], 南京理工大学, 中国, 2004)
|
[41]
|
Bosma R, van der Bergb J, Kaymakc U, Udod H, Verreth J. A generic methodology for developing fuzzy decision models. Expert Systems with Applications, 2012, 39(1): 1200-1210
|
[42]
|
Yu D J. Multi-criteria decision making based on generalized prioritized aggregation operators under intuitionistic fuzzy environment. International Journal of Fuzzy Systems, 2013, 15(1): 47-54
|
[43]
|
Dong G J, Zhou H F. Rough set method for remote sense image classification and information fusion. In: Proceedings of the 2010 International Conference on Computer Application and System Modeling (ICCASM 2010). Taiyuan, China: IEEE, 2010. 157-161
|
[44]
|
Wang Peng-Wei, Li Tao, Wu Xiu-Qing. An segmentation approach based on MRF and SVM posteriori probability. Journal of Remote Sensing, 2008, 12(2): 208-214 (王鹏伟, 李滔, 吴秀清. 一种基于SVM后验概率的MRF分割方法. 遥感学报, 2008, 12(2): 208-214)
|
[45]
|
Li Tao, Wang Jun-Pu, Wu Xiu-Qing, Tang Jin-Hui. Estimation of posterior probability and applications: an approach based on kernel logistic regression. Pattern Recognition and Artificial Intelligence, 2006, 19(6): 690-695 (李滔, 王俊普, 吴秀清, 唐金辉. 后验概率估计及其应用: 基于核Logistic 回归的方法. 模式识别与人工智能, 2006, 19(6): 690-695)
|
[46]
|
Jia Yong-Hong. Research on the Method of Multi-source Image Fusion and Its Application [Ph.D. dissertation], Wuhan University, China, 2001 (贾永红. 多源遥感影像数据融合方法及其应用的研究 [博士学位论文], 武汉大学, 中国, 2001)
|
[47]
|
Boudraa A O, Bentabet A, Salzenstein F, Guillon L. Dempster-Shafer's basic probability assignment based on fuzzy membership functions. Electronic Letters on Computer Vision and Image Analysis, 2004, 4(1): 1-9
|
[48]
|
Jiang W, Deng Y, Peng J Y. A new method to determine BPA in evidence theory. Journal of Computers, 2011, 6(6): 1162-1167
|
[49]
|
Zuo Z Y, Xu Y F, Chen G C. A new method of obtaining BPA and application to the bearing fault diagnoises of wind turbine. In: Proceedings of the 2009 International Symposium on Information Processing (ISIP'09). Huangshan, PR, China: IEEE, 2009. 368-371
|
[50]
|
Dai Guan-Zhong, Pan Quan, Zhang Shan-Ying, Zhang Hong-Cai. The developments and problems in evidence reasoning. Control Theory and Applications, 1999, 16(4): 465-469 (戴冠中, 潘泉, 张山鹰, 张洪才. 证据推理的进展及存在问题. 控制理论与应用, 1999, 16(4): 465-469)
|
[51]
|
Peng H P, Cao X J. Research conflict problems of D-S evidence and its application in multi-sensor information fusion technology. In: Proceedings of the 2010 IEEE International Conference on Information Theory and Information Security (ICITIS). Beijing, China: IEEE, 2010. 747-750
|
[52]
|
Zhou Zhe, Xu Xiao-Bin, Wen Cheng-Lin, Lv Feng. An optimal method for combining conflicting evidences. Acta Automatica Sinica, 2012, 38(6): 976-985 (周哲, 徐晓滨, 文成林, 吕峰. 冲突证据融合的优化方法. 自动化学报, 2012, 38(6): 976-985)
|
[53]
|
Zhu Jian-Ying. Some common key problems and their dealing methods in the application of fuzzy mathematical methods. Fuzzy Systems and Mathematics, 1992, 11(2): 57-63 (朱剑英. 应用模糊数学方法的若干关键问题及处理方法. 模糊系统与数学, 1992, 11(2): 57-63)
|
[54]
|
Yang C C, Bose N K. Generating fuzzy membership function with self-organizing feature map. Pattern Recognition Letters, 2006, 27(5): 356-365
|
[55]
|
Ang K K, Quek C. Supervised pseudo self-evolving cerebellar algorithm for generating fuzzy membership functions. Expert Systems with Applications, 2012, 39(3): 2279-2287
|
[56]
|
Ma J W, Hasi B. Remote sensing data classification using tolerant rough set and neural networks. Science in China Ser. D Earth Sciences, 2005, 48(12): 2251-2259
|
[57]
|
Deng Ting-Quan, Yang Cheng-Dong, Zhang Yue-Tong. Fuzzy similarity relation based variable precision fuzzy rough sets. CAAI Transactions on Intelligent Systems, 2012, 7(2): 148-152(邓廷权, 杨成东, 张月童. 模糊相似关系下变精度模糊粗糙集. 智能系统学报, 2012, 7(2): 148-152)
|
[58]
|
Chair Z, Varshney P K. Optimal data fusion in multiple sensor detection system. IEEE Transactions on AES, 1986, 22(1): 98-101
|
[59]
|
Thomopoulos S C, Papadakis I N, Sahinoglou H, Okello N N. Centralized and distributed hypothesis testing with structured adaptive networks and perceptron-type neural networks. SPIE, 1992, 1611(1): 35-51
|
[60]
|
Pawlak R J. A new neural network architecture for the fusion of independent sensor decision. SPIE, 1994, 2232: 521-525
|
[61]
|
Ni Guo-Qiang, Li Yong-Liang, Niu Li-Hong. New developments in data fusion technology based on neural network Journal of Beijing Institute of Technology, 2003, 23(4): 503-508 (倪国强, 李勇量, 牛丽红. 基于神经网络的数据融合技术的新进展. 北京理工大学报, 2003, 23(4): 503-508)
|
[62]
|
Yu X H, Xu Z S. Prioritized intuitionistic fuzzy aggregation operators. Information Fusion, 2013, 14(1): 108-116
|
[63]
|
Virrantaus K. Analysis of the uncertainty and imprecision of the source data sets for a military terrain analysis application. In: Proceedings of In: Proceedings of the 2nd International Symposium on Spatial Data Quality'03, Hong Kong, China, 2003. 139-145
|
[64]
|
Lee H, Lee B, Park K, Elmasri R. Fusion techniques for reliable information: a survey. International Journal of Digital Content Technology and Its Applications, 2010, 4(2): 74-88
|
[65]
|
Stein A, Hamm N A S, Ye Q G. Handing uncertainties in image mining for remote sensing studies. International Journal of Remote Sensing, 2009, 30(20): 5365-5382
|
[66]
|
Bombrun L, Vasile G, Gong M, Totir F. Hierarchical segmentation of polarimetric SAR images using heterogeneous cluster models. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(2): 726-737
|
[67]
|
Qi Yu-Juan, Wang Yan-Jiang, Li Yong-Ping. Memory-based Gaussian mixture background modeling. Acta Automatica Sinica, 2010, 36(11): 1520-1526 (齐玉娟, 王延江, 李永平. 基于记忆的混合高斯背景建模. 自动化学报, 2010, 36(11): 1520-1526)
|
[68]
|
Xiong Biao, Jiang Wan-Shou, Li Le-Lin. Gauss mixture model based semi-supervised classification for remote sensing image. Geomatics and Information Science of Wuhan University, 2011, 36(1): 108-112 (熊彪, 江万寿, 李乐林. 基于高斯混合模型的遥感影像半监督分类. 武汉大学学报: 信息科学版, 2011, 36(1): 108-112)
|
[69]
|
Xiao Jian-Yu, Tong Min-Ming, Zhu Chang-Jie, Wang Xiao-Lei. Basic probability assignment construction method based on generalized triangular fuzzy number. Chinese Journal of Scientific Instrument, 2012, 33(2): 429-434 (肖建于, 童敏明, 朱昌杰, 王小蕾. 基于广义三角模糊数的基本概率赋值构造方法. 仪器仪表学报, 2012, 33(2): 429-434)
|
[70]
|
Liang Fa-Mai, Zhang Jing, Wang Guo-Hong. Study on the method of constructing basic probability assignment function in targets identification. Fire Control and Command Control, 2008, 33(8): 8-11 (梁发麦, 张静, 王国宏. 雷达目标识别中获取基本概率赋值的方法. 火力与指挥控制, 2008, 33(8): 8-11)
|
[71]
|
Yang Jing-Hua, Yu Hua. Multi-Source Information Fusion Theory and Applications. Beijing: Beijing University of Posts and Telecommunications press, 2011(杨露菁, 余华. 多源信息融合理论与应用 (第2版). 北京: 北京邮电大学出版社, 2011)
|
[72]
|
Wanas N. Feature based Architecture for Decision Fusion [Ph.D. dissertation], University of Waterloo, Canada, 2003
|
[73]
|
Van Laere J. Challenges for IF performance evaluation in practice. In: Proceedings of the 12th International Conference on Information Fusion (FUSION'09). Seattle, WA: IEEE, 2009. 866-873
|
[74]
|
Shi Qiang, Chen Feng-E, Mei Tian-Can, Qin Qian-Qing. Remote sensing image segmentation based on SVM posterior probability and improved multi-scale MRF. Geomatics and Information Science of Wuhan University, 2013, 38(2): 193-199 (石强, 陈凤娥, 梅天灿, 秦前清. SVM 后验概率结合改进多尺度MRF的遥感影像分割方法. 武汉大学报信息科学版, 2013, 38(2): 193-199)
|
[75]
|
Zhu Jie-Hao, Zhou Jian-Jiang, Wu Jie. Radar target recognition based on semiparametric density estimation. Journal of Electronics and Information Technology, 2010, 32(9): 2161-2166 (朱劼昊, 周建江, 吴杰. 基于半参数化概率密度估计的雷达目标识别. 电子与信息学报, 2010, 32(9): 2161-2166)
|
[76]
|
Li Yan-Xin, Li Guang-Yu, Li Wen. Learning algorithm of membership functions based on RBF neural network. Journal of Dalian Jiaotong University, 2007, 28(2): 34-37 (李延新, 李光宇, 李文. 基于RBF 神经网络的隶属度函数学习算法. 大连交通大学学报, 2007, 28(2): 34-37)
|
[77]
|
Xu P D, Deng Y, Su X Y, Mahadevan S. A new method to determine basic probability assignment from training data. Knowledge-Based Systems, 2013, 46: 69-80
|
[78]
|
Zhu H, Basir O. A novel fuzzy evidential reasoning paradigm for data fusion with applications in image processing. Soft Computing Journal --- A Fusion of Foundations, Methodologies and Applications, 2006, 10(12): 1169-1180
|
[79]
|
Farah I R, Boulila W, Ettabaa K S, Solaiman B, Ahmed M B. Interpretation of multisensor remote sensing images: multiapproach fusion of uncertain information. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46(12): 4142-4152
|
[80]
|
Xu X B, Wen C L. Random sets: a unified framework for multisource information fusion. Journal of Electronics (China), 2009, 26(6): 723-730
|
[81]
|
Smarandache F. A Unifying Field in Logics: Neutrosophic Logic, Neutrosophy, Neutrosophic Set, Probability, and Statistics. Rehoboth: American Research Press, 2000
|
[82]
|
Han Chong-Zhao, Han De-Qiang, Jie Jing. From biological cognition and perception to methodologies of system engineering. Systems Engineering --- Theory and Practice, 2008, 6(Supplement): 75-93 (韩崇昭, 韩德强, 介婧. 从生物感知认知到系统工程方法论. 系统工程理论与实践, 2008, 6(增刊): 75-93)
|
[83]
|
Ni Guo-Qiang, Dai Wen, Li Yong-Liang, Pu Tian. Visual/IR color image fusion based on rattlesnake bimodal cell neurodynamics: advances and prospects. Journal of Beijing Institute of Technology, 2004, 24(2): 95-100 (倪国强, 戴文, 李勇量, 蒲恬. 基于响尾蛇双模式细胞机理的可见光/红外图像彩色融合技术的优势和前景展望. 北京理工大学学报, 2004, 24(2): 95-100)
|
[84]
|
Li X R. Optimal Bayes joint decision and estimation. In: Proceedings of the 10th International Conference on Information Fusion. Quebec, Que: IEEE, 2007. 874-881
|
[85]
|
Thomas C, Balikrishnan N. Modified evidence theory for performance enhancement of intrusion detection system. In: Proceedings of the 2008 IEEE International Conference on Information Fusion. Cologne: IEEE, 2008. 1-8
|
[86]
|
Wang Gang, Huang Li-Hua, Zhang Cheng-Hong. Review of hybrid intelligent systems. Journal of Systems Engineering, 2010, 25(4): 569-578 (王刚, 黄丽华, 张成洪. 混合智能系统研究综述. 系统工程学报, 2010, 25(4): 569-578)
|
[87]
|
Wozniak M, Grana M, Corchado E. A survey of multiple classifier systems as hybrid systems. Information Fusion, to be published
|
[88]
|
Castllo O, Melin P, Janusz K. Recent Advances on Hybrid Intelligent Systems. Berlin, Heidelberg: Springer-Verlag, 2013
|