油井远程夜视监控系统的研究与设计
|
摘要
随着多媒体技术、通信技术以及激光红外夜视技术的飞速发展,基于无线通信的远程夜视监控系统在变电站、森林防火、油田、煤矿等部门得到了广泛应用,论文结合胜利油田河口采油一矿安防的实际需求,提出了油井远程夜视监控系统的总体设计方案,对油井远程夜视监控系统的关键技术进行了深入研究,主要工作如下:
1、在现场调研的基础上,针对油井分布和夜间远距离监控的特点,论文进行了油井远程夜视监控系统的总体结构设计,完成了无线传输、监控中心、监控前端的软硬件配置和调试工作。现场运行表明,系统采用无线传输稳定可靠,油井预置位精度高,夜视监控效果良好,能准确、及时地发现目标,提高了油田的安防水平。
2、论文对红外图像形成机理进行了深入研究,总结了油井红外夜视图像的特点,针对部分夜视图像受天气环境影响比较模糊、对比度低的情况,在分析常用红外图像灰度变换算法优缺点的基础上,提出了基于自适应区间拉伸的夜视图像处理算法。实验表明该方法结合了油井图像自身的特点,变换增强效果稳定,使图像的对比度得到了较大的提高。
3、论文分析了图像噪声的种类、特点及模型,针对油井夜视图像存在的噪声特点,在借鉴标准中值滤波、均值滤波等算法的基础上,提出了一种自适应混合滤波的新算法。实验表明,该算法针对油井图像存在的不同噪声采用不同的处理方法,在去噪的同时很好地保护了图像的边缘及细节信息。
论文设计的油井远程夜视监控系统在油田应用良好,它所采用的夜视图像处理技术使模糊油井图像恢复得比较清晰,提高了油田安全生产管理水平,对油田监控方面的开发探索具有一定的参考价值。
Along with the rapid development of the multimedia technologies, the communication and the laser infrared night vision technologies, the remote night monitoring system based on wireless communication has been widely applied in transformer substation、the forest fire protection、the oil field、the coal mine and such various departments. According to the actual needs for security of Hekou First Oil Production Field of Shengli Oilfield, this paper proposes the remote oil well night monitoring system’s design program, and deeply researches the monitoring system’s key technologies. The main works are as follows:
1. Based on the oil field investigation and research, in view of the characteristics of oil well distribution and night long-distance monitoring, this thesis carries on the overall system structure design. It has completed the software/hardware configuration and debugging work for the wireless transmission, the monitoring center and monitoring front-end. The system operation indicates that with the wireless transmission, the system is stable and reliable, the oil well’s pre-setting precision is high, and the night monitoring effect is good. This system can discover the aim accurately and promptly, which enhances the security level of the oil field.
2. The paper researches the infrared image’s formation mechanism, and summarizes the infrared image’s characteristic. Because of the weather environmental influence, a part of the night images are vague and low contrast. By analyzing the common gray-scale transformation algorithms of infrared images, a new method is put forward—adaptive interval stretching algorithm. Experiments show that combined with image characteristics, this method has steady enhancement effect and improves image’s contrast greatly.
3. For the infrared night images’noise, this thesis analyzes the types, features and models of the noise. In the reference of standard median filtering, mean filtering algorithms, a new algorithm is proposed—adaptive mixed noise filtering. Experiments show that this improved algorithm can process different noise separately, while de-noising it also protects the edge information and details well.
The monitoring system is well applied in the oil field, and the night monitoring image processing technologies restore the fuzzy oil well images clearly, it has improved the production and security level of oil field. This system has certain reference value to the exploration of oil field monitoring.
1、在现场调研的基础上,针对油井分布和夜间远距离监控的特点,论文进行了油井远程夜视监控系统的总体结构设计,完成了无线传输、监控中心、监控前端的软硬件配置和调试工作。现场运行表明,系统采用无线传输稳定可靠,油井预置位精度高,夜视监控效果良好,能准确、及时地发现目标,提高了油田的安防水平。
2、论文对红外图像形成机理进行了深入研究,总结了油井红外夜视图像的特点,针对部分夜视图像受天气环境影响比较模糊、对比度低的情况,在分析常用红外图像灰度变换算法优缺点的基础上,提出了基于自适应区间拉伸的夜视图像处理算法。实验表明该方法结合了油井图像自身的特点,变换增强效果稳定,使图像的对比度得到了较大的提高。
3、论文分析了图像噪声的种类、特点及模型,针对油井夜视图像存在的噪声特点,在借鉴标准中值滤波、均值滤波等算法的基础上,提出了一种自适应混合滤波的新算法。实验表明,该算法针对油井图像存在的不同噪声采用不同的处理方法,在去噪的同时很好地保护了图像的边缘及细节信息。
论文设计的油井远程夜视监控系统在油田应用良好,它所采用的夜视图像处理技术使模糊油井图像恢复得比较清晰,提高了油田安全生产管理水平,对油田监控方面的开发探索具有一定的参考价值。
Along with the rapid development of the multimedia technologies, the communication and the laser infrared night vision technologies, the remote night monitoring system based on wireless communication has been widely applied in transformer substation、the forest fire protection、the oil field、the coal mine and such various departments. According to the actual needs for security of Hekou First Oil Production Field of Shengli Oilfield, this paper proposes the remote oil well night monitoring system’s design program, and deeply researches the monitoring system’s key technologies. The main works are as follows:
1. Based on the oil field investigation and research, in view of the characteristics of oil well distribution and night long-distance monitoring, this thesis carries on the overall system structure design. It has completed the software/hardware configuration and debugging work for the wireless transmission, the monitoring center and monitoring front-end. The system operation indicates that with the wireless transmission, the system is stable and reliable, the oil well’s pre-setting precision is high, and the night monitoring effect is good. This system can discover the aim accurately and promptly, which enhances the security level of the oil field.
2. The paper researches the infrared image’s formation mechanism, and summarizes the infrared image’s characteristic. Because of the weather environmental influence, a part of the night images are vague and low contrast. By analyzing the common gray-scale transformation algorithms of infrared images, a new method is put forward—adaptive interval stretching algorithm. Experiments show that combined with image characteristics, this method has steady enhancement effect and improves image’s contrast greatly.
3. For the infrared night images’noise, this thesis analyzes the types, features and models of the noise. In the reference of standard median filtering, mean filtering algorithms, a new algorithm is proposed—adaptive mixed noise filtering. Experiments show that this improved algorithm can process different noise separately, while de-noising it also protects the edge information and details well.
The monitoring system is well applied in the oil field, and the night monitoring image processing technologies restore the fuzzy oil well images clearly, it has improved the production and security level of oil field. This system has certain reference value to the exploration of oil field monitoring.
引文
[1]宋磊,黄祥林,沈兰荪.视频监控系统概述[J].测控技术,2003,(5):13- l5
[2]刘富强.数字视频监控系统开发及应用[M].北京:机械工业出版社,2003
[3]万家富等.网络监控系统原理与应用[M].北京:机械工业出版社,2003
[4]沈承东,谭庆平.基于MPEG-4的数字视频监控系统的设计和实现[J].计算机工程,2002,28(8)
[5]唐忆东.夜视技术发展综述[J].舰船光学,2004,40(2):15-17,42
[6]李嘉穗.红外技术在视频监控中的应用[J].中国公共安全,2007(12A):125-126
[7]王海峰.基于MPEG-4的嵌入式数字视频监控系统研究和设计[D].北京:北京交通大学,2007
[8]张鸣平,张敬贤,李玉丹.夜视系统[M].北京:北京理工大学出版社,1993:47-68
[9]赵丽,陈燎原,罗萃文.远程视频监控系统的安全可靠性技术[J].计算机应用,2003,23(12)
[10]王春华.基于无线局域网的视频监控系统的研究实现[D].北京:北京工业大学,2007
[11]曹贝贞,李志康,薛松.基于无线网络技术的数字视频监控系统[J].计算机工程,2007,(1):248
[12]马建峰,吴振强著.无线局域网安全体系结构[M].北京:高等教育出版社,2008
[13]赵纯,王洪亮.无线数字视频监控系统设计[J].仪表技术与传感器,2008,(10):46-48
[14]吴乐南.无线视频监控技术与展望[J].中国安防,2007,(9):58-61
[15]王艳平,张越.Windows网络与通信程序设计[M].北京:人民邮电出版社,2006
[16]丁展,刘海英等.Visual C++网络通信编程实用案例精选[M].北京:人民邮电出版社,2005
[17] Behrouz A. Forouzan.数据通信与网络[M].第三版.北京:机械工业出版社,2004
[18]李培燕.关于远程视频监控系统的研究[J].现代计算机,2002,(4)
[19]刘伟等.IP组播技术在远程视频监控系统中的应用[J].计算机应用研究,2002,(2)
[20]郭丽红,吴海涛.无人值守变电站远程视频监控系统的研究与应用[J].工业控制计算机,2008,21(3):31-32
[21]杨宜禾,岳敏.红外系统[M].国防工业出版社,1995
[22]吴宗凡.红外热像仪的原理和技术发展[J].光学及光电仪器,1997:28-30
[23]戴磊,魏宝刚.图像复原的算法研究[J].计算机工程与设计,2006,27(2):184-187
[24]吴元保,张江汉,谢勋碧.分布式数字视频监控系统的设计与实现[J].计算机工程.2006,(10):251
[25]吕潇超.数字视频监控系统研究与实现[D].西安:西北工业大学,2007
[26] (英)Maria Petrou,(希)Panagiota Bosdogianni.数字图像处理疑难解析[M].赖剑煌,冯国灿等译.北京:机械工业出版社,2005
[27] Kenneth R.Castleman.Digital Image Processing[M].北京:清华大学出版社,2003
[28]曹聚亮,吕海宝,李冠章.基于自适应局部灰度修正的直方图均匀算法[J].红外与激光工程,2004,33(5):513-515
[29]阮秋琦.数字图像处理学[M].电子工业出版社,2001
[30] Vese L,Osher S.Modeling textures with total variation minimization and oscillating patterns in image processing[C].Journal of Scientific Computing,2003
[31] Narasimhan S G, Nayar S K. Contrast restoration of weather degraded images[J]. Pattern Anal. Mach.1nlell,2003,25(6):7l3-724
[32]满家巨,沈军.一种图像噪声准确估计方法[J].湖南师范大学自然科学学报,2008(31):44-47
[33]徐航.基于DSP的夜视图像处理研究[D].长春:长春理工大学,2008
[34]杨词银,黄廉卿.基于幂函数的加权自适应直方图均衡[J].光电子·激光,2002,13(5):515-517
[35] Oakly J P,Satherley B L. Improving images quality in poor visibility conditions using physical model for degradation [J].IEEE Trans. on Image Processing,l998,7(2):l67-l79
[36] GONZALEZ R C,WOODS R E,EDDINS S L.数字图像处理(MATLAB版)[M].北京:电子工业出版社,2004
[37]徐飞,施晓红等.MATLAB应用图像处理[M].西安:西安电子科技大学出版社,2003
[38]王晓勇.中值滤波和同态滤波算法及其应用[D].上海:上海交通大学,2006
[39]清源计算机工作室. Matlab高级应用--图形及影像处理[M].北京:机械工业出版杜.2000
[40]徐军等.一种红外图像增强的新方法[J].西安电子科技大学学报(自然科学版),2000,27(5)
[41] Rafael C.Gonzalez, Richard E.Woods著,阮秋琦,阮宇智译.数字图像处理[M].第二版.电子工业出版社,2003
[42] G.Deng, L.W. Cahill, G.R.Tobin. The study of logarithmic image processing model and its application to image enhancement[J].IEEE Trans.Im age Processing,1995,4(4):506-512
[43] D .Mukherjee, B.N.Chatterji.Adaptive neighborhood extended contrast enhancement and its modifications[J].Graphical medals and image processing,1995,57(3):254-265
[44] H.Zhu, F.H.Y Chan, F.K.Lam. Image contrast enhancement by constrained local histogram equalization[J].Computer vision and image understanding,1999,73(2):281-290
[45] Tao Chen, Kai-Kuang Ma, Li-Hui Chen. Tri-state median filter for image denoising[J].IEEE Trans. Image processing.1999,8:1834-1838
[46]林晓春,王艳.一种基于图像融合的红外图像增强新方法[J].红外技术,2004,26(2)
[47] T.L.Ji, M.K.Sundaershan, H.Roehrig. Adaptive image contrast enhancement based on human visual properties[J]. IEEE Transactions on Medical Imaging,1994,13(4):573-586
[48]李学广.红外图像预处理算法研究及硬件实现[D].哈尔滨:哈尔滨工程大学,2007
[49]史彩成等.基于模糊理论的红外图像滤波[J].激光与红外,2001,31(2):113-114
[50]徐军等.一种红外图像增强的新方法[J].西安电子科技大学学报(自然科学版),2000,27(5)
[51]陈钱等.红外图像直方图双向均衡技术研究[J].红外与毫米波学报,2003,22(6):428-430
[52]吴宗凡.红外热像仪的原理和技术发展[J].光学及光电仪器,1997:28-30
[53]盛道清.图像增强算法的研究[D].武汉:武汉科技大学,2007
[54] Lin Yin, Ruikang Yang, Moncef Gabbouj,YrJO Neuvo.Weighted Median Filters: Tutorial.IEEE Transaction on circuits and systems-Ⅱ: Analog and digital signal processing,1996,43:157-191
[55] H.Zhu, Image Contrast Enhancement by Constrained Local Histogram Equalization[J].Computer Vision and Image Understanding,1999,73(2)
[56]王磊.红外图像增强算法研究及其实时实现技术[D].西安:西安电子科技大学,2007
[57] G Deng, L.W.Cahill, G.R.Tobin. The study of logarithmic image processing model and its application to image enhancement[J].IEEE Trans. Image Processing,1995,4(4):506-512
[58] Stark. J.A. Adaptive Image Contrast Enhancement Using Generalization of Histogram equalization[J].IEEE Transactions on Image Processing,2000,9(5):889-896
[2]刘富强.数字视频监控系统开发及应用[M].北京:机械工业出版社,2003
[3]万家富等.网络监控系统原理与应用[M].北京:机械工业出版社,2003
[4]沈承东,谭庆平.基于MPEG-4的数字视频监控系统的设计和实现[J].计算机工程,2002,28(8)
[5]唐忆东.夜视技术发展综述[J].舰船光学,2004,40(2):15-17,42
[6]李嘉穗.红外技术在视频监控中的应用[J].中国公共安全,2007(12A):125-126
[7]王海峰.基于MPEG-4的嵌入式数字视频监控系统研究和设计[D].北京:北京交通大学,2007
[8]张鸣平,张敬贤,李玉丹.夜视系统[M].北京:北京理工大学出版社,1993:47-68
[9]赵丽,陈燎原,罗萃文.远程视频监控系统的安全可靠性技术[J].计算机应用,2003,23(12)
[10]王春华.基于无线局域网的视频监控系统的研究实现[D].北京:北京工业大学,2007
[11]曹贝贞,李志康,薛松.基于无线网络技术的数字视频监控系统[J].计算机工程,2007,(1):248
[12]马建峰,吴振强著.无线局域网安全体系结构[M].北京:高等教育出版社,2008
[13]赵纯,王洪亮.无线数字视频监控系统设计[J].仪表技术与传感器,2008,(10):46-48
[14]吴乐南.无线视频监控技术与展望[J].中国安防,2007,(9):58-61
[15]王艳平,张越.Windows网络与通信程序设计[M].北京:人民邮电出版社,2006
[16]丁展,刘海英等.Visual C++网络通信编程实用案例精选[M].北京:人民邮电出版社,2005
[17] Behrouz A. Forouzan.数据通信与网络[M].第三版.北京:机械工业出版社,2004
[18]李培燕.关于远程视频监控系统的研究[J].现代计算机,2002,(4)
[19]刘伟等.IP组播技术在远程视频监控系统中的应用[J].计算机应用研究,2002,(2)
[20]郭丽红,吴海涛.无人值守变电站远程视频监控系统的研究与应用[J].工业控制计算机,2008,21(3):31-32
[21]杨宜禾,岳敏.红外系统[M].国防工业出版社,1995
[22]吴宗凡.红外热像仪的原理和技术发展[J].光学及光电仪器,1997:28-30
[23]戴磊,魏宝刚.图像复原的算法研究[J].计算机工程与设计,2006,27(2):184-187
[24]吴元保,张江汉,谢勋碧.分布式数字视频监控系统的设计与实现[J].计算机工程.2006,(10):251
[25]吕潇超.数字视频监控系统研究与实现[D].西安:西北工业大学,2007
[26] (英)Maria Petrou,(希)Panagiota Bosdogianni.数字图像处理疑难解析[M].赖剑煌,冯国灿等译.北京:机械工业出版社,2005
[27] Kenneth R.Castleman.Digital Image Processing[M].北京:清华大学出版社,2003
[28]曹聚亮,吕海宝,李冠章.基于自适应局部灰度修正的直方图均匀算法[J].红外与激光工程,2004,33(5):513-515
[29]阮秋琦.数字图像处理学[M].电子工业出版社,2001
[30] Vese L,Osher S.Modeling textures with total variation minimization and oscillating patterns in image processing[C].Journal of Scientific Computing,2003
[31] Narasimhan S G, Nayar S K. Contrast restoration of weather degraded images[J]. Pattern Anal. Mach.1nlell,2003,25(6):7l3-724
[32]满家巨,沈军.一种图像噪声准确估计方法[J].湖南师范大学自然科学学报,2008(31):44-47
[33]徐航.基于DSP的夜视图像处理研究[D].长春:长春理工大学,2008
[34]杨词银,黄廉卿.基于幂函数的加权自适应直方图均衡[J].光电子·激光,2002,13(5):515-517
[35] Oakly J P,Satherley B L. Improving images quality in poor visibility conditions using physical model for degradation [J].IEEE Trans. on Image Processing,l998,7(2):l67-l79
[36] GONZALEZ R C,WOODS R E,EDDINS S L.数字图像处理(MATLAB版)[M].北京:电子工业出版社,2004
[37]徐飞,施晓红等.MATLAB应用图像处理[M].西安:西安电子科技大学出版社,2003
[38]王晓勇.中值滤波和同态滤波算法及其应用[D].上海:上海交通大学,2006
[39]清源计算机工作室. Matlab高级应用--图形及影像处理[M].北京:机械工业出版杜.2000
[40]徐军等.一种红外图像增强的新方法[J].西安电子科技大学学报(自然科学版),2000,27(5)
[41] Rafael C.Gonzalez, Richard E.Woods著,阮秋琦,阮宇智译.数字图像处理[M].第二版.电子工业出版社,2003
[42] G.Deng, L.W. Cahill, G.R.Tobin. The study of logarithmic image processing model and its application to image enhancement[J].IEEE Trans.Im age Processing,1995,4(4):506-512
[43] D .Mukherjee, B.N.Chatterji.Adaptive neighborhood extended contrast enhancement and its modifications[J].Graphical medals and image processing,1995,57(3):254-265
[44] H.Zhu, F.H.Y Chan, F.K.Lam. Image contrast enhancement by constrained local histogram equalization[J].Computer vision and image understanding,1999,73(2):281-290
[45] Tao Chen, Kai-Kuang Ma, Li-Hui Chen. Tri-state median filter for image denoising[J].IEEE Trans. Image processing.1999,8:1834-1838
[46]林晓春,王艳.一种基于图像融合的红外图像增强新方法[J].红外技术,2004,26(2)
[47] T.L.Ji, M.K.Sundaershan, H.Roehrig. Adaptive image contrast enhancement based on human visual properties[J]. IEEE Transactions on Medical Imaging,1994,13(4):573-586
[48]李学广.红外图像预处理算法研究及硬件实现[D].哈尔滨:哈尔滨工程大学,2007
[49]史彩成等.基于模糊理论的红外图像滤波[J].激光与红外,2001,31(2):113-114
[50]徐军等.一种红外图像增强的新方法[J].西安电子科技大学学报(自然科学版),2000,27(5)
[51]陈钱等.红外图像直方图双向均衡技术研究[J].红外与毫米波学报,2003,22(6):428-430
[52]吴宗凡.红外热像仪的原理和技术发展[J].光学及光电仪器,1997:28-30
[53]盛道清.图像增强算法的研究[D].武汉:武汉科技大学,2007
[54] Lin Yin, Ruikang Yang, Moncef Gabbouj,YrJO Neuvo.Weighted Median Filters: Tutorial.IEEE Transaction on circuits and systems-Ⅱ: Analog and digital signal processing,1996,43:157-191
[55] H.Zhu, Image Contrast Enhancement by Constrained Local Histogram Equalization[J].Computer Vision and Image Understanding,1999,73(2)
[56]王磊.红外图像增强算法研究及其实时实现技术[D].西安:西安电子科技大学,2007
[57] G Deng, L.W.Cahill, G.R.Tobin. The study of logarithmic image processing model and its application to image enhancement[J].IEEE Trans. Image Processing,1995,4(4):506-512
[58] Stark. J.A. Adaptive Image Contrast Enhancement Using Generalization of Histogram equalization[J].IEEE Transactions on Image Processing,2000,9(5):889-896