多传感器图像融合技术综述

毛士艺; 赵巍

多传感器图像融合技术综述

毛士艺,
赵巍

北京航空航天大学电子工程系

详细信息

作者简介:
毛士艺(1935-),男,浙江黄岩人,教授,100083,北京.

中图分类号: TN 911.73
计量
- 文章访问数: 4028
- HTML全文浏览量: 235
- PDF下载量: 2822
- 被引次数: 0
出版历程
- 收稿日期: 2002-03-17
- 网络出版日期: 2002-05-31

Comments on Multisensor Image Fusion Techniques

Beijing University of Aeronautics and Astronautics, Dept. of Electronic Engineering

摘要

摘要: 对国内外多传感器图像融合技术的发展状况进行了介绍,描述了图像融合的主要步骤,概括了目前主要图像融合方法的基本原理,并对各种方法的性能进行了定性分析.给出了评价图像融合效果的标准和方法,指出了图像融合技术的发展方向.
- 图像处理 /
- 图像合成 /
- 传感器 /
- 图像融合
Abstract: Multisensor image fusion is included in multisensor information fusion and has been applied widely. The techniques of image fusion are different from general information fusion techniques because of the particularity of images.The development condition about the multisensor image fusion is introduced firstly. Secondly, the main steps in image fusion process are described and the combinations of different sensors are given. The main image fusion methods, including multiresolution image fusion methods, methods based on wavelet and false color methods etc., are discussed. The performance of every method is analyzed qualitatively. The criteria how to evaluate image fusion method are given and the development directions of image fusion are pointed out finally.
- image processing /
- image composite /
- sensors /
- image fusion

HTML全文

参考文献(1)

[1] 郁文贤, 雍少为, 郭桂蓉. 多传感器信息融合技术述评[J]. 国防科技大学学报, 1994, 16(3):1~11. [2]王泽和. 九十年代美海军潜艇传感器融合系统[J]. 现代军事, 1992, 7:74~77. [3]Bhogal A S, Goodenough D G, Dyk A, et al. Extraction of forest attribute information using multisensor data fusion techniques:A case study for a test site on Vancouver island, British Columbia. In:IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing, 2001. 674~680. [4]Liu Q J, Takeuchi N. Vegetation inventory of a temperate biosphere reserve in China by image fusion of Landsat TM and SPOT HRV[J]. Journal of Forest Research, 2001, 6(3):139~146. [5]陈东, 李飚, 沈振康. SAR与可见光图像融合算法的研究[J]. 系统工程与电子技术, 2000, 22(9):5~7. [6]Kropas-Hughes C V. Image fusion using autoassociative-heteroassociative neural networks. USA:Air University,1999. [7]朱晓松, 茅耀斌, 戴跃伟, 等. 一种基于HVS的小波水印方案[J]. 南京理工大学学报, 2001,25(3):262~268. [8]Valet L, Mauris G, Bolon Ph. A statistical overview of recent literature in information fusion[J]. IEEE AESS Systems Magazine, 2001,16(3):7~14. [9]蒋晓瑜. 基于小波变换和伪彩色方法的多重图像融合算法研究. 北京:北京理工大学光电工程系, 1997. [10] 胡江华, 柏连发, 张保民. 像素级多传感器图像融合技术[J]. 南京理工大学学报, 1996,20(5):453~456. [11]张加友,王江安. 红外图像融合[J]. 光电子·激光, 2000, 11(5):537~539. [12]Meek T R. Multiresolution image fusion of thematic mapper imagery with synthetic aperture radar imagery. USA:Utah State University, 1999. [13]Burt P J, Kolczynski R J. Enhanced image capture through fusion. In:IEEE 4th International Conf on Computer Vision, 1993, 4. 173~182. [14]allier E, Farooq M. A real time pixel-level based image fusion via adaptive weight averaging. In:Proceedings of the 3rd International Conference on Information Fusion, 2000, 2. 3~13. [15]金红, 刘榴娣. 彩色空间变换法在图像融合中的应用[J]. 光学技术,1997(4):44~48. [16]Nú ez J, Otazu X, Fors O, et al. Multiresolution-based image fusion with additive wavelet decomposition[J]. IEEE Transaction on Geoscience and Remote Sensing, 1999, 37(3):1204~1211. [17]Burt P J, Adelson E H. The Laplacian pyramid as a compact image code. IEEE Transactions on Communications, 1983, COM-31(4):532~540. [18]Toet A. Multiscale contrast enhancement with applications to image fusion[J]. Optical Engineering, 1992, 31(5):1026~1031. [19]Toet A, Ruyven L J, Valeton J M. Merging thermal and visual images by a contrast pyramid[J]. Optical Engineering, 1989, 28(7):789~792. [20]蒲恬, 倪国强. 应用于图像融合中的多尺度对比调制法[J]. 北京理工大学学报, 2000,20(2):119~223. [21]Toet A. A morphological pyramid image decomposition[J]. Pattern Recognition Letters, 1989, 9(4):255~261. [22]Aiazzi B, Alparone L, Barducci A, et al. Multispectral fusion of multisensor image data by the generalized Laplacian pyramid. In:IEEE International Geoscience and Remote Sensing Symposium, 1999,2. 1183~1185. [23]Aiazzi B, Alparone L, Argenti F. Multisensor image fusion by frequency spectrum substitution:subband and multirate approaches for a 3:5 scale ratio case. In:IEEE International Geoscience and Remote Sensing Symposium, 2000,6. 2629~2631. [24]Argenti F, Alparone L. Filterbanks design for multisensor datafusion. IEEE Signal Processing Letters, 2000,7(5):100~103. [25]刘贵喜, 杨万海. 一种像素级多算子红外与可见光图像融合方法[J]. 红外与毫米波学报,2001, 20(3):207~210. [26]Wu Xiuqing, Zhou Rong, Xu Yunxiang. A method of wavelet-based edge detection with data fusion for mutiple images. In:Proceedings of the 3rd World Congress on Intelligent Control and Automation, 2000. 2691~2694. [27]陈勇, 皮德富, 周士源,等. 基于小波变换的红外图像融合技术研究[J]. 红外与激光工程, 2001,30(1):15~17. [28]杨火亘, 杨万海, 裴继红. 基于小波分解的不同聚焦点图像融合方法[J]. 电子学报, 2001,29(6):846~848. [29]崔岩梅, 倪国强, 王毅,等. 一种基于小波变换的多尺度多算子图像融合方法. 光学技术,1999(4):37~39. [30]李树涛, 王耀南. 基于树状小波分解的多传感器图像融合[J]. 红外与毫米波学报, 2001, 20(3):119~222. [31]Nikolov S G, Bull D R, Canagarajah C N. 2-D image fusion by multiscale edge graph combination. In:Proc of the 3rd International Conference on Information Fusion, 2000, 1. 16~22. [32]Mallat S, Zhang S. Characterization of signal from multiscale edges[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992, 14(7):710~732. [33]Nikoukhah B R, Willsky A S. Multiscale system theory. In:Proc 29th IEEE Conference on Decision and Control, 1990.2484~2487. [34]Chou K, Willsky A S, Benveniste A. Multiscale recursive estimation, data fusion and regularization[J]. IEEE Trans on Automatic Control, 1994,39(3):464~478. [35]Basseville M, Benveniste A, Chou K, et al. Modeling and estimation of multiresolution stochastic process[J]. IEEE Trans on Information Theory, 1992,38(2):766~784. [36]Ho T T. Multiscale modeling and estimation of large-scale dynamic systems. Cambridge:Massachusetts Institute of Technology, 1998. [37]Simone G, Morabito F C, Farina A. Radar image fusion by multiscale Kalman filtering. In:Proc of the 3rd International Conference on Information Fusion, 2000,2.10~17. [38]Simone G, Morabito F C, Farina A. Multifrequency and multiresolution fusion of SAR images for remote sensing applications. In:Proc of the 4th International Conference on Information Fusion, 2001. [39]Toet A, Walraven J. New false color mapping for image fusion[J]. Optical engineering, 1996,35(3):650~658. [40]Fay D A, Waxman A M, Verly J G, et al. Fusion of visible, infrared and 3D LADAR imagery. In:Proc of the 4th International Conference on Information Fusion, 2001. [41]Waxman A M, Lazott C, Fay D A, et al. Neural processing of SAR imagery for enhanced target detection. In:Proc of SPIE on Algorithms for Synthetic Aperture Radar Imagery Ⅱ, 1995,2487. 201~210. [42]Waxman A M, Gove A, Seibert M C, et al. Progress on color night vision:visible/IR fusion, perception and search, and low-light CCD images. In:Proc of SPIE Conf on Enhanced and Synthetic Vision, 1996,2736. 96~107. [43]Fay D A, Waxman A M, Ireland D B, et al. Fusion of multi-sensor imagery for night vision:color visualization, target learning and search. In:Proc of the 3rd International Conference on Information Fusion, 2000,1.3~10. [44]Fay D A, Waxman A M, Aguilar M, et al. Fusion of 2-/3-/4-sensor imagery for visualization, target learning and search. In:Proc of SPIE on Enhanced and Synthetic Vision, 2000,4023.106~115. [45]Waxman A M, Fay D A, Gove A, et al. Color night vision:fusion of intensified visible and thermal IR imagery. In:Proc of SPIE on Synthetic Vision for Vehicle Guidance and Control, 1995,2463.58~68. [46]Waxman A M, Savoye E D, Fay D A, et al. Electronic imaging aids for night driving:low-light CCD, uncooled thermal IR, and color fused visible/LWIR. In:Proc of SPIE on Transportation Sensors and Controls:Collsion Avoidance Traffic Management and ITS, 1997,2902.62~73. [47]Streilein W, Waxman A M, Ross W, et al. Fused multi-sensor image mining for feature foundation data. In:Proc of the 3rd International Conference on Information Fusion, 2000,1.18~25. [48]Aguilar M, Fay D A, Ireland D B, et al. Field evaluations of dual-band fusion for color night vision. In:Pro of SPIE Conf on Enhanced and Synthetic Vision, 1999,3691.168~175. [49]Ross W D, Waxman A M, Streilein W, et al. Multi-sensor 3D image fusion and interactive search. In:Proc of the 3rd International Conference on Information Fusion, 2000, 1.10~17. [50]Waxman A M, Verly J, Fay D A, et al. A prototype system for 3D color fusion and mining of multisensor/ spectral imagery. In:Proce of the 4th International Conference on Information Fusion, 2001. [51]Aguilar M, Fay D A, Ross W D, et al. Real-time fusion of low-light CCD and uncooled IR imagery for color night vision. In:Proc SPIE Conf on Enhanced and Synthetic Vision, 1998,3364.124~135. [52]Waxman A M, Gove A, Fay D A, et al. Color night vision:opponent processing in the fusion of visible and IR imagery[J]. Neural Networks Letter, 1997,10(1):1~6. [53]Toet A, Ijspeert J K, Waxman A M, et al. Fusion of visible and thermal imagery improves situational. In:Proc SPIE Conf on Enhanced and Synthetic Vision, 1997,3088.177~188. [54]Steele P M, Perconti P. Part task in investigation of multispectral image fusion using gray scale and synthetic color night vision sensor imagery for helicopter pilotage. In:Proc of SPIE on Targets and Backgrounds:Characterization and Representation, 1997,3062.88~100. [55]Xydaes C, Petrovi V. Objective image fusion performance measure[J]. Electronic Letters,2000,36(4):308~309. [56]Petrovi V, Xydaes C. On the effects of sensor noise in pixel-level image fusion performance. In:Proc of the 3rd International Conference on Information Fusion, 2000,2.14~19. [57]崔岩梅, 倪国强, 钟堰利, 等. 利用统计特性进行图像融合效果分析及评价[J].北京理工大学学报, 2000, 20(1):102~106.

施引文献

资源附件(0)

访问统计