基于红外目标检测的DSP实现
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摘要
基于红外图像的目标检测技术是现代光电子技术领域的重要组成部分。红外成像系统因为具有良好的抗干扰能力，能透过烟雾等障碍探测到目标，实现昼夜连续工作，所以红外检测系统可以作为雷达等探测系统的补充，在船舶避碰、海岸监视和交通管理中发挥重要作用。
本文在算法理论、系统软件设计和硬件实现等几个方面进行了研究。论文的第一部分对海面背景下的运动目标检测算法进行了研究，通过对运动目标检测算法的分析比较，提出了一种基于Sobel算子的帧间差分检测算法。传统的帧间差分法算法简单、便于硬件实现，但在信噪比较低时抗噪性能较差。而本文研究的中等距离船舶目标，与点目标相比具有一定的边缘特征，因此将边缘检测与帧间差分相接合便可获得良好的抗噪性能。文中对多种边缘检测算子进行了分析比较，其中Sobel算子在处理该类图像时的速度与效果比较理想，且算法简单易于DSP硬件实现，所以最终采用了sobel算子。本文第二部分分析了DSP在图像处理中的优势，详细介绍了其片内外设EDMA在系统中的应用，设计了基于TMS320C6711 DSP的红外船舶目标检测系统的硬件电路，并在该平台上实现了基于Sobel算子的图像检测算法。系统软件采用C语言编写，并根据C6711的硬件特征进行了优化，优化后运行效果良好。
由于应用的特殊性，本文在研究过程中还特别注意了算法的实时性，在软硬件配合优化后，算法实时性能达到应用要求。用DSP实现检测算法对于系统的小型化、便携化很有意义，因此，本文对于构建船舶目标实时检测系统有一定的价值。
Target detection and recognition technology on infrared image is an important part in modern photoelectron technology field. With good jamming performance, infrared imaging system can detect target through such obstacles as smoke, dust, fog, etc. and realize continuous passive detection day and night. So, infrared detection and recognition system can serve as a supplement to radar and other detection and it will play an important role in ship collision prevention, ship navigation safety, and Vessel Traffic Service.
This dissertation has finished algorithm analysis and has designed the ship target detection system. Algorithm has been realized on the software and hardware, and ship target can be detection accurately. The first part of dissertation studied the algorithms of moving target detection in sea-background. By analysis and comparison the algorithms, the dissertation presented an algorithm, based on the Sobel operator and frame difference method. Considering the characteristics of infrared image, the frame difference algorithm is simple and easy to be realized by hardware. But the algorithm' anti-noise performance is not well while the signal-to-noise ratio is low. Compared with the point target, the moving ship target captured at intermediate range has certain edge characteristic. So by joining the edge detection algorithm and the frame difference the algorithm can obtain better anti-noise performance. By comparing several edge detection operators, it considered that the Sobel operator has higher processing speed and better performance and easier realized by DSP. In the second part, this dissertation analyzed the superiority of DSP in image processing and particularly introduced the application of EDMA in system. Based on the TMS320C6711 DSP,
本文在算法理论、系统软件设计和硬件实现等几个方面进行了研究。论文的第一部分对海面背景下的运动目标检测算法进行了研究，通过对运动目标检测算法的分析比较，提出了一种基于Sobel算子的帧间差分检测算法。传统的帧间差分法算法简单、便于硬件实现，但在信噪比较低时抗噪性能较差。而本文研究的中等距离船舶目标，与点目标相比具有一定的边缘特征，因此将边缘检测与帧间差分相接合便可获得良好的抗噪性能。文中对多种边缘检测算子进行了分析比较，其中Sobel算子在处理该类图像时的速度与效果比较理想，且算法简单易于DSP硬件实现，所以最终采用了sobel算子。本文第二部分分析了DSP在图像处理中的优势，详细介绍了其片内外设EDMA在系统中的应用，设计了基于TMS320C6711 DSP的红外船舶目标检测系统的硬件电路，并在该平台上实现了基于Sobel算子的图像检测算法。系统软件采用C语言编写，并根据C6711的硬件特征进行了优化，优化后运行效果良好。
由于应用的特殊性，本文在研究过程中还特别注意了算法的实时性，在软硬件配合优化后，算法实时性能达到应用要求。用DSP实现检测算法对于系统的小型化、便携化很有意义，因此，本文对于构建船舶目标实时检测系统有一定的价值。
Target detection and recognition technology on infrared image is an important part in modern photoelectron technology field. With good jamming performance, infrared imaging system can detect target through such obstacles as smoke, dust, fog, etc. and realize continuous passive detection day and night. So, infrared detection and recognition system can serve as a supplement to radar and other detection and it will play an important role in ship collision prevention, ship navigation safety, and Vessel Traffic Service.
This dissertation has finished algorithm analysis and has designed the ship target detection system. Algorithm has been realized on the software and hardware, and ship target can be detection accurately. The first part of dissertation studied the algorithms of moving target detection in sea-background. By analysis and comparison the algorithms, the dissertation presented an algorithm, based on the Sobel operator and frame difference method. Considering the characteristics of infrared image, the frame difference algorithm is simple and easy to be realized by hardware. But the algorithm' anti-noise performance is not well while the signal-to-noise ratio is low. Compared with the point target, the moving ship target captured at intermediate range has certain edge characteristic. So by joining the edge detection algorithm and the frame difference the algorithm can obtain better anti-noise performance. By comparing several edge detection operators, it considered that the Sobel operator has higher processing speed and better performance and easier realized by DSP. In the second part, this dissertation analyzed the superiority of DSP in image processing and particularly introduced the application of EDMA in system. Based on the TMS320C6711 DSP,
引文
[1] 李斌，彭嘉雄．基于动态规划的红外小目标检测与识别[J]．华中理工大学学报，2000，28(6)
[2] 柯丽、黄廉卿“DSP芯片在实时图像处理系统中的应用” 光机电信息，2005．1
[3] Barron J. Fleet D. Beauchemin S. Performance of optical flow techniques. International Journal of Computer Vision. 1994, 12(1):42-77
[4] Iketani A, Kuno Y. Shimada N. et al. Real time Surveillance System Detecting Persons in Complex Scenes. In Proceedings of Image Analysis and Processing, 1999 1112-1115
[5] Davis L, Philomin V and Duraiswami R. Tracking humans from a moving platform. 15th int. Conf. on Pattern Recognition. Vol.4, pp. 171-78, 2000.
[6] 徐向辉．红外图像目标检测与跟踪研究：[学位论文]．北京：北京理工大学，2001
[7] 杜峥．红外弱小运动目标检测与跟踪方法研究[D]．武汉：华中科技大学；2003．4
[8] BauchHE, FuttermanWI, KemmerDB. Back-ground suppression and tracking with as taring mosaic sensor[J]. Optical Engineering. 1981,20(1):103～110.
[9] IranniM,etal.,Detectioin and tracking multiple moving objects using temporal integration[A]. Second European Confer on Computer Vision[C], Italy: Santa Margherita Ligure, 1992.282～287.
[10] 李宏贵，李兴国．基于分形特征的红外图像识别方法[J]．红外与激光工程，1999，28(1)
[11] 姜锦锋．红外图像的目标检测、识别与跟踪技术研究[D]．西北工业大学；2004．3
[12] 何斌、马天予、王运坚，《数字图像处理》北京人民邮电出版社，2002．12
[13] 陈书海、傅录祥，《数字图像处理》科学出版社，2005．6
[14] Fujiyoshi H and Lipton A. Real-time human motion analysis by image skeletonization. In Proceedings of the IEEE Workshop on Applications of Computer Vison, 1998.
[15] 王永仲、郭豪、何永强“基于TMS320C6203DSP的实时红外图像处理系统”红外技术，2004．9
[16] Andrew Bateman, lain Paterson - Stephens "The DSP Handbook—Algorithm, Applications and Design Techniques" 机械工业出版社2003
[17] 任丽香，马淑芬，李方慧．TMS3206000系列DSPs的原理与应用．北京电子工业出版社2000
[18] 赵训威，TMS320C6200系列DSPS芯片应用与开发，北京人民邮电出版社，2002．
[19] TMS320C62x/67x CPU and Instruction Set[Z]. Reports of Texas Instruments[R], Owensville, MO,USA: Custom Printing Company,1998(3)
[20] 周霖，《信号处理技术应用》国防工业出版社，2004．1
[21] TMS320C6000 CPU and Instruction Set Reference Guide, Copyright, Texas Instruments Incorporated, October 2000
[22] 吴海勇、曹杰郑、剑泉，《用EDMA传输数字视频信号》，电子产品世界2003．5
[23] TMS320C6000 Peripherals Reference Guide, Texas Instruments. 2001.
[24] Code Composer Studio White Paper. Tex as Instruments In corporated, 1999
[25] Code Composer Studio User's Guide, Texas Instruments Incorporated,1999-2000
[26] 彭启棕、管庆，《DSP集成开发环境》，电子工业出版社，2004．7
[27] Li Xiang Ren. The Principle and Application of TMS320C6000 DSPS. Publishing House of Electronics Industry,2000
[28] TMS320C6000 Optimizing Compiler User's Guide, Reports of Texas Instruments[R], Owensville, MO,USA: Custom Printing Company, 1999(4)
[29] 田元、叶秀清、顾伟康“实时图像处理系统中的DSP优化编程”电子技术，2000．10
[30] TMS320C6000 DSP Cache User's Guide, Copyright, Texas Instruments Incorporated, May 2003
[31] 曹炬一、谭毅华、马杰、田金文“从移动背景红外序列图像中检测运动目标”电子与信息学报，2005．1
[32] 王东峰，多模态和大型图像配准技术研究[博士论文]，中国科学院电子学研究 所，2002．5
[33] Kenneth．R．Castleman，数字图像处理[M]，电子工业出版社，1998．9
[34] 王强，基于轮廓的多源图像配准技术研究〔硕士论文〕，华中科技大学，2002．5
[35] 陈宁红，图像配准的稳健性研究，上海交通大学博士论文，2001
[36] TMS320C621x/C671x DSP Two-Level Internal Memory Reference Guide, Copyright, Texas Instruments Incorporated, June 2004
[37] 刘其真，姚剑，孙薇，何永保．红外成像运动目标识别与跟踪方法研究[J]．遥感技术与应用，1999，14(2)
[38] 王迅、周建忠、欧阳艺“海上目标红外特征的选取方法研究”光电技术应用，2004．9
[39] 孙少军，王学伟．舰载红外成像探测跟踪系统仿真研究[J]．光电技术应用，2004，19(3)
[2] 柯丽、黄廉卿“DSP芯片在实时图像处理系统中的应用” 光机电信息，2005．1
[3] Barron J. Fleet D. Beauchemin S. Performance of optical flow techniques. International Journal of Computer Vision. 1994, 12(1):42-77
[4] Iketani A, Kuno Y. Shimada N. et al. Real time Surveillance System Detecting Persons in Complex Scenes. In Proceedings of Image Analysis and Processing, 1999 1112-1115
[5] Davis L, Philomin V and Duraiswami R. Tracking humans from a moving platform. 15th int. Conf. on Pattern Recognition. Vol.4, pp. 171-78, 2000.
[6] 徐向辉．红外图像目标检测与跟踪研究：[学位论文]．北京：北京理工大学，2001
[7] 杜峥．红外弱小运动目标检测与跟踪方法研究[D]．武汉：华中科技大学；2003．4
[8] BauchHE, FuttermanWI, KemmerDB. Back-ground suppression and tracking with as taring mosaic sensor[J]. Optical Engineering. 1981,20(1):103～110.
[9] IranniM,etal.,Detectioin and tracking multiple moving objects using temporal integration[A]. Second European Confer on Computer Vision[C], Italy: Santa Margherita Ligure, 1992.282～287.
[10] 李宏贵，李兴国．基于分形特征的红外图像识别方法[J]．红外与激光工程，1999，28(1)
[11] 姜锦锋．红外图像的目标检测、识别与跟踪技术研究[D]．西北工业大学；2004．3
[12] 何斌、马天予、王运坚，《数字图像处理》北京人民邮电出版社，2002．12
[13] 陈书海、傅录祥，《数字图像处理》科学出版社，2005．6
[14] Fujiyoshi H and Lipton A. Real-time human motion analysis by image skeletonization. In Proceedings of the IEEE Workshop on Applications of Computer Vison, 1998.
[15] 王永仲、郭豪、何永强“基于TMS320C6203DSP的实时红外图像处理系统”红外技术，2004．9
[16] Andrew Bateman, lain Paterson - Stephens "The DSP Handbook—Algorithm, Applications and Design Techniques" 机械工业出版社2003
[17] 任丽香，马淑芬，李方慧．TMS3206000系列DSPs的原理与应用．北京电子工业出版社2000
[18] 赵训威，TMS320C6200系列DSPS芯片应用与开发，北京人民邮电出版社，2002．
[19] TMS320C62x/67x CPU and Instruction Set[Z]. Reports of Texas Instruments[R], Owensville, MO,USA: Custom Printing Company,1998(3)
[20] 周霖，《信号处理技术应用》国防工业出版社，2004．1
[21] TMS320C6000 CPU and Instruction Set Reference Guide, Copyright, Texas Instruments Incorporated, October 2000
[22] 吴海勇、曹杰郑、剑泉，《用EDMA传输数字视频信号》，电子产品世界2003．5
[23] TMS320C6000 Peripherals Reference Guide, Texas Instruments. 2001.
[24] Code Composer Studio White Paper. Tex as Instruments In corporated, 1999
[25] Code Composer Studio User's Guide, Texas Instruments Incorporated,1999-2000
[26] 彭启棕、管庆，《DSP集成开发环境》，电子工业出版社，2004．7
[27] Li Xiang Ren. The Principle and Application of TMS320C6000 DSPS. Publishing House of Electronics Industry,2000
[28] TMS320C6000 Optimizing Compiler User's Guide, Reports of Texas Instruments[R], Owensville, MO,USA: Custom Printing Company, 1999(4)
[29] 田元、叶秀清、顾伟康“实时图像处理系统中的DSP优化编程”电子技术，2000．10
[30] TMS320C6000 DSP Cache User's Guide, Copyright, Texas Instruments Incorporated, May 2003
[31] 曹炬一、谭毅华、马杰、田金文“从移动背景红外序列图像中检测运动目标”电子与信息学报，2005．1
[32] 王东峰，多模态和大型图像配准技术研究[博士论文]，中国科学院电子学研究 所，2002．5
[33] Kenneth．R．Castleman，数字图像处理[M]，电子工业出版社，1998．9
[34] 王强，基于轮廓的多源图像配准技术研究〔硕士论文〕，华中科技大学，2002．5
[35] 陈宁红，图像配准的稳健性研究，上海交通大学博士论文，2001
[36] TMS320C621x/C671x DSP Two-Level Internal Memory Reference Guide, Copyright, Texas Instruments Incorporated, June 2004
[37] 刘其真，姚剑，孙薇，何永保．红外成像运动目标识别与跟踪方法研究[J]．遥感技术与应用，1999，14(2)
[38] 王迅、周建忠、欧阳艺“海上目标红外特征的选取方法研究”光电技术应用，2004．9
[39] 孙少军，王学伟．舰载红外成像探测跟踪系统仿真研究[J]．光电技术应用，2004，19(3)