图像融合在视频交通信息检测中的应用研究
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摘要
近年来,智能交通系统(ITS)产业在世界范围内蓬勃发展,视频交通信息检测系统是ITS的重要组成部分,它利用图像处理的方法采集交通管理所需要的信息。针对信息采集的需要,本文研究了基于小波分析的图像融合算法及其在交通检测系统中的应用,目的在于提高智能交通系统的服务质量。
图像融合技术是当代数字图像处理领域的前沿课题之一,而目前基于小波变换的图像融合技术是信息融合领域的热点问题。
本文首先简要介绍了国内外视频交通信息检测系统的发展概况及系统的设计方案;然后,对小波变换和图像融合的基本理论、方法及现状做了详细阐述;最后,讨论了基于小波变换的图像融合算法及其在视频交通信息检测系统中的应用。论文重点研究了区域化图像融合设计方案,即在设计视频车辆检测系统时,针对小波图像融合算法计算量大、难以实时处理的难点,只对虚拟检测线覆盖的图像区域进行融合,而不处理与车辆检测无关的区域。与对整幅图像进行的融合相比,区域化图像融合只关注感兴趣区域的图像信息,具有运算量小等特点,适用于对实时性要求高的系统。实验表明,将区域化图像融合应用于视频交通信息检测系统,较好地解决了小波图像融合算法计算量大难以进行实时视频处理的难题。
实验结果表明,论文工作研究的区域化图象融合车辆检测算法有效地提高了检测系统的检测正确率,具有较大的应用价值。
Recent years, Intelligent Transportation System (ITS) technology has made a great progress worldwide. The Video Traffic Information Detection System is an important part of the ITS. The system is used to acquire any needed information of traffic management using image processing technology. For the need of information acquiring, an image fusion scheme based on the wavelet transform are researched, aiming for improving the quality of the system.
Image fusion is one of the advanced subjects both in the field of digital image processing and in that of data fusion. The image fusion based on wavelet transform is popular at the present time.
Firstly, the paper introduces the general situation of the development of the ITS both in domestic and overseas. Then, the theory and methods of wavelet transform and image fusion are discussed in detail. Finally, the application of wavelet theory in image fusion scheme was analyzed, it was also used for ITS.
A design proposal of partition image fusion is brought forward in this dissertation. Focusing on the computational complexity of wavelet domain image fusion algorithm and its low real-time capability, this dissertation proposes a new method that fuses the given partition of images which is covered by the virtual detection line and ignores the the rest partition of this image. Comparing with fusion of the whole image, the partition image fusion has low computational complexity. Experimental results show that partition image fusion method applied in the vehicle detection system not only improves the image quality, but also meets the time-constraints of system requirements.
The result of experiment indicates that the computational complexity of wavelet domain image fusion algorithm which is researched in dissertation improves the accuracy rate of detection system effectively, and it also has great value in application.
图像融合技术是当代数字图像处理领域的前沿课题之一,而目前基于小波变换的图像融合技术是信息融合领域的热点问题。
本文首先简要介绍了国内外视频交通信息检测系统的发展概况及系统的设计方案;然后,对小波变换和图像融合的基本理论、方法及现状做了详细阐述;最后,讨论了基于小波变换的图像融合算法及其在视频交通信息检测系统中的应用。论文重点研究了区域化图像融合设计方案,即在设计视频车辆检测系统时,针对小波图像融合算法计算量大、难以实时处理的难点,只对虚拟检测线覆盖的图像区域进行融合,而不处理与车辆检测无关的区域。与对整幅图像进行的融合相比,区域化图像融合只关注感兴趣区域的图像信息,具有运算量小等特点,适用于对实时性要求高的系统。实验表明,将区域化图像融合应用于视频交通信息检测系统,较好地解决了小波图像融合算法计算量大难以进行实时视频处理的难题。
实验结果表明,论文工作研究的区域化图象融合车辆检测算法有效地提高了检测系统的检测正确率,具有较大的应用价值。
Recent years, Intelligent Transportation System (ITS) technology has made a great progress worldwide. The Video Traffic Information Detection System is an important part of the ITS. The system is used to acquire any needed information of traffic management using image processing technology. For the need of information acquiring, an image fusion scheme based on the wavelet transform are researched, aiming for improving the quality of the system.
Image fusion is one of the advanced subjects both in the field of digital image processing and in that of data fusion. The image fusion based on wavelet transform is popular at the present time.
Firstly, the paper introduces the general situation of the development of the ITS both in domestic and overseas. Then, the theory and methods of wavelet transform and image fusion are discussed in detail. Finally, the application of wavelet theory in image fusion scheme was analyzed, it was also used for ITS.
A design proposal of partition image fusion is brought forward in this dissertation. Focusing on the computational complexity of wavelet domain image fusion algorithm and its low real-time capability, this dissertation proposes a new method that fuses the given partition of images which is covered by the virtual detection line and ignores the the rest partition of this image. Comparing with fusion of the whole image, the partition image fusion has low computational complexity. Experimental results show that partition image fusion method applied in the vehicle detection system not only improves the image quality, but also meets the time-constraints of system requirements.
The result of experiment indicates that the computational complexity of wavelet domain image fusion algorithm which is researched in dissertation improves the accuracy rate of detection system effectively, and it also has great value in application.
引文
[1]朱东辉,智能交通系统的发展,山东交通学院学报,2002,10(4):9~14
[2]黄卫,陈里德,智能运输系统概论,北京:人民交通出版社,2001
[3]翁剑成,翟雅峤,赵晓娟,综合交通信息平台的交通基础数据库设计,中国交通信息产业,2009,135~137
[4]S. Takaba, M.Sakauchi, T. Kaneko. Measurement of Traffic Flow Using Real Time Processing of Moving Pictures. In: 32nd Conference on Vehicular Technology. 1982, 488~494
[5]W. Dichinson, R. C. Waterfall. Video Image Processing for Monitoring Road Traffic. In: IEEE International Conference on Road Traffic Data Collection. 1984, 105~109
[6]李伟,像素级图像融合方法及应用研究:[博士学位论文],广东:华南理工大学,2006
[7]Texas Instruments. In: TMS320DM642 Video/Imaging Fixed-Point Digital Signal Processor. 21~22
[8]Texas Instruments. In: TMS320DM642 Technical Overview. 13~14
[9]Texas Instruments. In: TMS320C6000 DSP Peripheral Component Interconnect (PCI) Reference Guide. 17~19
[10]李方慧,TMS320C6000系列DSPs原理与应用,北京:电子工业出版社,2003
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[12]李房惠,王飞,何佩琨等,TMS320C6000系列DSPs原理与应用(第二版),北京:电子工业出版社,2003
[13]江思敏,刘畅,TMS320C6000 DSP应用开发教程,北京:机械工业出版社,2005,41~72
[14]胡昌华,李国华,刘涛等,基于MATLAB6.x的系统分析与设计-小波分析,西安:西安电子科技大学出版社,2004,1~4
[15]崔锦泰,小波分析导论,西安:西安交通大学出版社,1995, 1~3
[16]R.C.冈萨雷斯,R.E.伍兹,数字图像处理(阮秋琦等译),北京:电子工业出版社,2006, 288~295
[17]Mallat S. G. A Theory for Multiresolution Signal Decomposition: The Wavelet Representation, In: IEEE Transaction on Pattern Analysis and Machine Intelligence. 1989, 11(7):674~693
[18]程正兴,小波分析算法与应用,西安:西安交通大学出版社,2000
[19] BrownL.G, A survey of image registration techniques, ACM Computing Surveys, 325~376
[20]BalterJ, Pelizzari C.,Chen G. Correlation of projection radiographs in radiation therapy using open curve segments and points.MedPhys,1992, 329~334
[21]王智均,李德仁,李清泉,Wallis变换在小波影像融合中的应用,武汉测绘科技大学学报,2000, 338~342
[22]余松提,周源华,吴时光,数字图像处理,北京:电子工业出版社,1989,89~116
[23]郭雷,李晖晖,鲍永生,图像融合,北京:电子工业出版社,1995
[24]Gonzalez R.C., WinsztP. Digital image processing Addsion-Wesleg Publishing Company Inc, 1977, 45~52
[25]敬忠良,肖刚,李振华,图像融合理论与应用,北京:高等教育出版社,2007,47~52
[26]Xydaes C., Petrovo V. Objective Image Fusion Performance Measure. In: Electronic Letters. 2000, 36(4):1939~1949
[27]C.S. Xydeas, V. Petrovi?. Objective Image Fusion Performance Measure. In: Electronics Letters. 2000, 36(4):308~309
[28]C.S. Xydeas, V.S. Petrovi?. Objective Pixel-level Image Fusion Performance Measure. In: Proceedings of SPIE. 2000, 4051:89~98
[29]Piella G. New Quality Measures for Image Fusion. In: 7th International Conference on Information Fusion. 2004, 542~546
[30]陶冰洁,王敬儒,采用小波分析的图像融合方法评述,计算机工程与应用,2005,25:16~19
[31]赵有星,李京,基于小波变换的图像融合方法综述,计算机与信息技术,2007,29:413~414
[32]李卫华,数字图像预处理与融合方法研究:[博士学位论文],西安:西北工业大学,2006
[33]张流,基于DSP的视频车辆检测系统设计:[硕士学位论文],天津:天津大学,2005
[2]黄卫,陈里德,智能运输系统概论,北京:人民交通出版社,2001
[3]翁剑成,翟雅峤,赵晓娟,综合交通信息平台的交通基础数据库设计,中国交通信息产业,2009,135~137
[4]S. Takaba, M.Sakauchi, T. Kaneko. Measurement of Traffic Flow Using Real Time Processing of Moving Pictures. In: 32nd Conference on Vehicular Technology. 1982, 488~494
[5]W. Dichinson, R. C. Waterfall. Video Image Processing for Monitoring Road Traffic. In: IEEE International Conference on Road Traffic Data Collection. 1984, 105~109
[6]李伟,像素级图像融合方法及应用研究:[博士学位论文],广东:华南理工大学,2006
[7]Texas Instruments. In: TMS320DM642 Video/Imaging Fixed-Point Digital Signal Processor. 21~22
[8]Texas Instruments. In: TMS320DM642 Technical Overview. 13~14
[9]Texas Instruments. In: TMS320C6000 DSP Peripheral Component Interconnect (PCI) Reference Guide. 17~19
[10]李方慧,TMS320C6000系列DSPs原理与应用,北京:电子工业出版社,2003
[11]Texas Instruments. In: TMS320C6000 Code Composer Studio Tutorial, 1~3
[12]李房惠,王飞,何佩琨等,TMS320C6000系列DSPs原理与应用(第二版),北京:电子工业出版社,2003
[13]江思敏,刘畅,TMS320C6000 DSP应用开发教程,北京:机械工业出版社,2005,41~72
[14]胡昌华,李国华,刘涛等,基于MATLAB6.x的系统分析与设计-小波分析,西安:西安电子科技大学出版社,2004,1~4
[15]崔锦泰,小波分析导论,西安:西安交通大学出版社,1995, 1~3
[16]R.C.冈萨雷斯,R.E.伍兹,数字图像处理(阮秋琦等译),北京:电子工业出版社,2006, 288~295
[17]Mallat S. G. A Theory for Multiresolution Signal Decomposition: The Wavelet Representation, In: IEEE Transaction on Pattern Analysis and Machine Intelligence. 1989, 11(7):674~693
[18]程正兴,小波分析算法与应用,西安:西安交通大学出版社,2000
[19] BrownL.G, A survey of image registration techniques, ACM Computing Surveys, 325~376
[20]BalterJ, Pelizzari C.,Chen G. Correlation of projection radiographs in radiation therapy using open curve segments and points.MedPhys,1992, 329~334
[21]王智均,李德仁,李清泉,Wallis变换在小波影像融合中的应用,武汉测绘科技大学学报,2000, 338~342
[22]余松提,周源华,吴时光,数字图像处理,北京:电子工业出版社,1989,89~116
[23]郭雷,李晖晖,鲍永生,图像融合,北京:电子工业出版社,1995
[24]Gonzalez R.C., WinsztP. Digital image processing Addsion-Wesleg Publishing Company Inc, 1977, 45~52
[25]敬忠良,肖刚,李振华,图像融合理论与应用,北京:高等教育出版社,2007,47~52
[26]Xydaes C., Petrovo V. Objective Image Fusion Performance Measure. In: Electronic Letters. 2000, 36(4):1939~1949
[27]C.S. Xydeas, V. Petrovi?. Objective Image Fusion Performance Measure. In: Electronics Letters. 2000, 36(4):308~309
[28]C.S. Xydeas, V.S. Petrovi?. Objective Pixel-level Image Fusion Performance Measure. In: Proceedings of SPIE. 2000, 4051:89~98
[29]Piella G. New Quality Measures for Image Fusion. In: 7th International Conference on Information Fusion. 2004, 542~546
[30]陶冰洁,王敬儒,采用小波分析的图像融合方法评述,计算机工程与应用,2005,25:16~19
[31]赵有星,李京,基于小波变换的图像融合方法综述,计算机与信息技术,2007,29:413~414
[32]李卫华,数字图像预处理与融合方法研究:[博士学位论文],西安:西北工业大学,2006
[33]张流,基于DSP的视频车辆检测系统设计:[硕士学位论文],天津:天津大学,2005