图像拼接技术研究
|
摘要
图像拼接技术是数字图像处理领域的一个重要的研究分支,它将一组相互间存在重叠部分的图像序列进行匹配对准,重新注册融合后,形成一幅包含各图像序列信息的宽视角场景的新图像。图像拼接可以用来建立宽视角的高分辨率图像,在虚拟现实领域、医学图像处理领域、遥感技术领域和军事领域中均有广泛的应用。
本文首先介绍了图像拼接技术的意义、研究背景、研究现状及拼接技术的特点等,从而展示了图像拼接技术广泛的应用前景。然后对图像拼接的基本流程和关键技术做了概括和总结,重点介绍了图像拼接技术中的图像配准和图像融合等技术,分析和总结了目前主流的配准和融合方法。论文重点研究了模板匹配法和相位相关法,并针对传统方法的不足提出了改进的方法。
针对传统模板匹配法中亮度对拼接造成干扰的问题,本文提出了基于Lab颜色空间下的模板匹配。Lab颜色空间下可以很容易的将亮度从像素中分离出来,只对a、b颜色分量进行差值计算,实验证明可以有效避免亮度带来的干扰。另外在对应比较区域中采用了设定阈值随机取点的方法,避免了将所有对应点进行颜色差值计算,提高了拼接速度。
针对传统相位相关法中亮度对拼接造成干扰的问题,本文采用了基于轮廓的相位相关法。首先提取待拼接图像的二值轮廓图,然后对轮廓图进行相位相关计算,实验证明可以有效的避免亮度带来的干扰。另外在δ函数阵列最大峰值的选取中采用了迭代法二次计算寻找峰值,实验证明,这样可以有效的降低多个峰值带来的干扰。
Image mosaics technology is an important research branch of digital image processing. It carries on the spatial matching to a series of image overlapped with each other, and finally builds a seamless image with higher resolution and bigger eyeshot compared with a single image. Moreover, image mosaics technology can be used to construct the large field of view and high-resolution image, and widely applied to virtual reality, medical image processing, remote sensing and military affairs.
The thesis first introduces the background of image mosaics technology with great potential, and then demonstrates its characteristics and present research directions. In the second chapter, the author discusses the basic steps of image mosaic. Furthermore, the two pivotal methods of image mosaic, which are the image registration methods and images fusion methods, are introduced respectively. In the third and forth chapter, the thesis analyzes several traditional algorithms, such as the template matching and phase correlation algorithm. Moreover, in order to improve the above-mentioned algorithms, the modified methods are proposed backwards.
Specifically, in the traditional template matching algorithm, light intensity always interferes with image mosaic. A modified template matching algorithm in the Lab color space is proposed to solve the problem. In the Lab color space, it is so convenient to divide the light intensity from pixels that we just need calculate the difference between color values a and b. The results show that the proposed method can significantly attenuate the interferences due to the light intensity. On the other hand, random points within the threshold are selected and calculated in a quite small region, rather than the whole region, which largely reduces the complexity and increases the calculation speed.
To further reduce the interference from the light intensity, a contour phase correlation algorithm has been adopted. After picking up the binary image, a contour phase correlation is calculated to achieve the desired image. For another, when finding the maximum peak of the Dirac function array, we propose an iterative method with higher accuracy. The results of the experiments have significance for application in image mosaics technology.
本文首先介绍了图像拼接技术的意义、研究背景、研究现状及拼接技术的特点等,从而展示了图像拼接技术广泛的应用前景。然后对图像拼接的基本流程和关键技术做了概括和总结,重点介绍了图像拼接技术中的图像配准和图像融合等技术,分析和总结了目前主流的配准和融合方法。论文重点研究了模板匹配法和相位相关法,并针对传统方法的不足提出了改进的方法。
针对传统模板匹配法中亮度对拼接造成干扰的问题,本文提出了基于Lab颜色空间下的模板匹配。Lab颜色空间下可以很容易的将亮度从像素中分离出来,只对a、b颜色分量进行差值计算,实验证明可以有效避免亮度带来的干扰。另外在对应比较区域中采用了设定阈值随机取点的方法,避免了将所有对应点进行颜色差值计算,提高了拼接速度。
针对传统相位相关法中亮度对拼接造成干扰的问题,本文采用了基于轮廓的相位相关法。首先提取待拼接图像的二值轮廓图,然后对轮廓图进行相位相关计算,实验证明可以有效的避免亮度带来的干扰。另外在δ函数阵列最大峰值的选取中采用了迭代法二次计算寻找峰值,实验证明,这样可以有效的降低多个峰值带来的干扰。
Image mosaics technology is an important research branch of digital image processing. It carries on the spatial matching to a series of image overlapped with each other, and finally builds a seamless image with higher resolution and bigger eyeshot compared with a single image. Moreover, image mosaics technology can be used to construct the large field of view and high-resolution image, and widely applied to virtual reality, medical image processing, remote sensing and military affairs.
The thesis first introduces the background of image mosaics technology with great potential, and then demonstrates its characteristics and present research directions. In the second chapter, the author discusses the basic steps of image mosaic. Furthermore, the two pivotal methods of image mosaic, which are the image registration methods and images fusion methods, are introduced respectively. In the third and forth chapter, the thesis analyzes several traditional algorithms, such as the template matching and phase correlation algorithm. Moreover, in order to improve the above-mentioned algorithms, the modified methods are proposed backwards.
Specifically, in the traditional template matching algorithm, light intensity always interferes with image mosaic. A modified template matching algorithm in the Lab color space is proposed to solve the problem. In the Lab color space, it is so convenient to divide the light intensity from pixels that we just need calculate the difference between color values a and b. The results show that the proposed method can significantly attenuate the interferences due to the light intensity. On the other hand, random points within the threshold are selected and calculated in a quite small region, rather than the whole region, which largely reduces the complexity and increases the calculation speed.
To further reduce the interference from the light intensity, a contour phase correlation algorithm has been adopted. After picking up the binary image, a contour phase correlation is calculated to achieve the desired image. For another, when finding the maximum peak of the Dirac function array, we propose an iterative method with higher accuracy. The results of the experiments have significance for application in image mosaics technology.
引文
[1]L.G. Brown. A survey of image registration techniques. ACM Computer Surveys.1992.24(4). 325-376
[2]Chang Li, Jinlai Guo, Yu Xia. Image Auto-Mosaic for Large Angle of Obliquity Close-Range Sequential Images to Realize Cyber City. 2008 International Symposiums on ISIP. 2008.384-388
[3]P.R.Wolf. Elements of Phothgrammetry. McGraw-Hill. New York.1983.
[4]S.K.Nayar. Catadioptric Omnidirectional Camera. Proc. Computer Vision and Pattern Recognition(CVPR'97). IEEE CS Press. Los Alamitos, Calif.1997.428-488.
[5]Yu Liu, Junchan Du, Feng Ji. Design of Panoramic Mosaic Surveillance Platform in Severe Circumstance.2010 Third International Symposium on IITSI.2010.77-80
[6]A. Can, C.V. Stewart, B. Roysam. Robust hierarchical algorithm for constructing a mosaic from images of the curved human retina. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.1999.286-292
[7]Guosheng Yang, Huanlong Zhang, Yulin Yang. Study of Image Mosaic Based on the Method of Finite Difference. Proceedings of the 2008 Congress on Image and Signal Porcessing. 2008.436-440
[8]谢凯,郭恒业,张田文.图像Mosaics技术综述.软件学报.2004
[9]Richard Szeliski. Video Mosaics for Virtual Environments. IEEE Computer Graphics and Applications.1996.16(2).22-30.
[10]Zoghlami I., Faugeras O., Deriche R. Using geometric coners to build a 2D mosaic from a set of images. Computer Vision and Pattern Recognition. IEEE Computer Society Conference. 1997 Proceedings.420-425
[11]Xianyong Fang, Mingmin Zhang, Zhigeng Pan, Peng Wang. Manifold Mosaic with Large Displacement Images,13th Pacific Conference on Computer Graphics and Applications(PG2005)
[12]Deriche R., Blaszka T. Recovering and characterizing image features using an efficient model based approach. Computer Vision and Pattern Recognition. IEEE Computer Society Conference.1993 Proceedings.530-535
[13]Fernando N. Ventura, Leila M. G. Fonseca. Remotely Sensed Image Fusion Using The Wavelet Transform
[14]Peleg S., Rousso B., Rav-Acha A. Mosaicing on adaptive manifolds. Pattern Analysis and Machine Intelligence. IEEE Transactions.2000.22(10).1144-1154
[15]王伟,陆配忠.数字图像拼接技术综述.小型微型计算机系统.2006.27(7)
[16]C.Kuglin, D.Hines. The Phase Correlation Image alignment Method. IEEE Int. Conf. on Cybernetics and Society.1975.163-165
[17]Barbara Zitova, Jan Flusser. Image registration methods:a survey. Image and Vision Computing.21 (2003).977-1000
[18]Kanazawa Y and Kanatani K. Image mosaicing by stratified mathching. Image and Vision Computing.2004.22(2).93-103
[19]Noirfalise E, Laprest J T, June F and Dhome M. Real-time registration for image mosaicing. In Electronic Porc. of The 13th BMVC. University of Cardiff. September 2002.617-625
[20]Rafael C. Gonzalez, Richard E. Woods.阮秋琦,阮宇智.数字图像处理.第二版.北京.电子工业出版社.2006年11月.154-166
[21]陈书海,傅录祥.实用数字图像处理.第一版.北京.科学出版社.2005年6月.56-64
[22]Maria Petrou. Panagiota Bosdogianni.赖剑煌,冯国灿.数字图像处理疑难解析.第一版.北京.机械工业出版社.2005年11月.49-50
[23]尚明姝,谢凯.一种基于特征的全自动图像拼接算法.中国图象图形学报：A辑.2006
[24]王红梅,张科,李言俊.图像匹配研究进展.计算机工程与应用.2004.42-44
[25]陈果,左洪福.显微图像的一种快速拼接算法.仪器仪表学报.2003.24(4).343-347
[26]倪国强.多波段图像融合算法研究及其新发展.光电子技术与信息.2001.14(5).11-17
[27]Lu Peizhong, Wu Lide. Double hierarchical algorithm for video mosaics IEEE Pacific R im Conference on Multimedia.2001.206-213.
[28]李忠新,茅耀斌,王执铨.基于对数极坐标映射的图像拼接方法.中国图象图形学报：A辑.2005
[29]N.R. Wanigasekara,曾勇勤.多组视频流的实时图象拼接.中国图象图形学报：A辑.2003
[30]李立鸿,施鹏飞,赵群飞.基于多分辨率技术的快速全景图图像匹配算法.中国图象图形学报：A辑.2006
[31]邓宝松,宋汉辰,杨冰,吴玲达.基于仿射迭代模型的特征点匹配算法.中国图象图形学报：A辑.2007
[32]王年,范益政,韦穗,梁栋.基于图的Laplace谱的特征匹配.中国图象图形学报：A辑.2006
[33]沈海平,达飞鹏,雷家勇.基于最小二乘法的点云数据拼接研究.中国图象图形学报：A辑.2005
[34]赵辉,陈辉,于泓.一种改进的全景图自动拼接算法.中国图象图形学报：A辑.2007
[35]肖甫,吴慧中,肖亮,汤杨.一种光照鲁棒的图像拼接融合算法.中国图象图形学报：A辑.2007
[36]赵向阳,杜利民.一种全自动稳健的图像拼接融合算法.中国图象图形学报：A辑.2004
[37]赵万金,龚声蓉,刘全,沈向军,刘纯平.一种用于图像拼接的图像序列自动排序算法.中国图象图形学报：A辑.2007
[38]段瑞玲,李庆祥,李玉和.图像边缘检测方法研究综述.光学技术.2005.31(3).415-419
[39]殷润民,李伯虎,柴旭东.自适应柱状全景图拼接.中国图象图形学报：A辑.2008
[40]罗钟铉,刘成明.灰度图像匹配的快速算法.计算机辅助设计与图形学学报.2005
[41]孙远,周刚慧,赵立初,施鹏飞.灰度图像匹配的快速算法.计算机辅助设计与图形学学报.2000
[42]彭文,童若峰,钱归平,董金祥.使用特征点与曲线配准医学图像.计算机辅助设计与图形学学报.2007
[43]周骥,石教英,赵友兵.图像特征点匹配的强壮算法.计算机辅助设计与图形学学报.2006
[44]李艳丽,向辉.稳健的球面全景图全自动生成算法.计算机辅助设计与图形学学报.2007
[45]倪国强,刘琼.多源图像配准技术分析与展望.光电工程.2004,31(9)：1～6
[2]Chang Li, Jinlai Guo, Yu Xia. Image Auto-Mosaic for Large Angle of Obliquity Close-Range Sequential Images to Realize Cyber City. 2008 International Symposiums on ISIP. 2008.384-388
[3]P.R.Wolf. Elements of Phothgrammetry. McGraw-Hill. New York.1983.
[4]S.K.Nayar. Catadioptric Omnidirectional Camera. Proc. Computer Vision and Pattern Recognition(CVPR'97). IEEE CS Press. Los Alamitos, Calif.1997.428-488.
[5]Yu Liu, Junchan Du, Feng Ji. Design of Panoramic Mosaic Surveillance Platform in Severe Circumstance.2010 Third International Symposium on IITSI.2010.77-80
[6]A. Can, C.V. Stewart, B. Roysam. Robust hierarchical algorithm for constructing a mosaic from images of the curved human retina. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.1999.286-292
[7]Guosheng Yang, Huanlong Zhang, Yulin Yang. Study of Image Mosaic Based on the Method of Finite Difference. Proceedings of the 2008 Congress on Image and Signal Porcessing. 2008.436-440
[8]谢凯,郭恒业,张田文.图像Mosaics技术综述.软件学报.2004
[9]Richard Szeliski. Video Mosaics for Virtual Environments. IEEE Computer Graphics and Applications.1996.16(2).22-30.
[10]Zoghlami I., Faugeras O., Deriche R. Using geometric coners to build a 2D mosaic from a set of images. Computer Vision and Pattern Recognition. IEEE Computer Society Conference. 1997 Proceedings.420-425
[11]Xianyong Fang, Mingmin Zhang, Zhigeng Pan, Peng Wang. Manifold Mosaic with Large Displacement Images,13th Pacific Conference on Computer Graphics and Applications(PG2005)
[12]Deriche R., Blaszka T. Recovering and characterizing image features using an efficient model based approach. Computer Vision and Pattern Recognition. IEEE Computer Society Conference.1993 Proceedings.530-535
[13]Fernando N. Ventura, Leila M. G. Fonseca. Remotely Sensed Image Fusion Using The Wavelet Transform
[14]Peleg S., Rousso B., Rav-Acha A. Mosaicing on adaptive manifolds. Pattern Analysis and Machine Intelligence. IEEE Transactions.2000.22(10).1144-1154
[15]王伟,陆配忠.数字图像拼接技术综述.小型微型计算机系统.2006.27(7)
[16]C.Kuglin, D.Hines. The Phase Correlation Image alignment Method. IEEE Int. Conf. on Cybernetics and Society.1975.163-165
[17]Barbara Zitova, Jan Flusser. Image registration methods:a survey. Image and Vision Computing.21 (2003).977-1000
[18]Kanazawa Y and Kanatani K. Image mosaicing by stratified mathching. Image and Vision Computing.2004.22(2).93-103
[19]Noirfalise E, Laprest J T, June F and Dhome M. Real-time registration for image mosaicing. In Electronic Porc. of The 13th BMVC. University of Cardiff. September 2002.617-625
[20]Rafael C. Gonzalez, Richard E. Woods.阮秋琦,阮宇智.数字图像处理.第二版.北京.电子工业出版社.2006年11月.154-166
[21]陈书海,傅录祥.实用数字图像处理.第一版.北京.科学出版社.2005年6月.56-64
[22]Maria Petrou. Panagiota Bosdogianni.赖剑煌,冯国灿.数字图像处理疑难解析.第一版.北京.机械工业出版社.2005年11月.49-50
[23]尚明姝,谢凯.一种基于特征的全自动图像拼接算法.中国图象图形学报：A辑.2006
[24]王红梅,张科,李言俊.图像匹配研究进展.计算机工程与应用.2004.42-44
[25]陈果,左洪福.显微图像的一种快速拼接算法.仪器仪表学报.2003.24(4).343-347
[26]倪国强.多波段图像融合算法研究及其新发展.光电子技术与信息.2001.14(5).11-17
[27]Lu Peizhong, Wu Lide. Double hierarchical algorithm for video mosaics IEEE Pacific R im Conference on Multimedia.2001.206-213.
[28]李忠新,茅耀斌,王执铨.基于对数极坐标映射的图像拼接方法.中国图象图形学报：A辑.2005
[29]N.R. Wanigasekara,曾勇勤.多组视频流的实时图象拼接.中国图象图形学报：A辑.2003
[30]李立鸿,施鹏飞,赵群飞.基于多分辨率技术的快速全景图图像匹配算法.中国图象图形学报：A辑.2006
[31]邓宝松,宋汉辰,杨冰,吴玲达.基于仿射迭代模型的特征点匹配算法.中国图象图形学报：A辑.2007
[32]王年,范益政,韦穗,梁栋.基于图的Laplace谱的特征匹配.中国图象图形学报：A辑.2006
[33]沈海平,达飞鹏,雷家勇.基于最小二乘法的点云数据拼接研究.中国图象图形学报：A辑.2005
[34]赵辉,陈辉,于泓.一种改进的全景图自动拼接算法.中国图象图形学报：A辑.2007
[35]肖甫,吴慧中,肖亮,汤杨.一种光照鲁棒的图像拼接融合算法.中国图象图形学报：A辑.2007
[36]赵向阳,杜利民.一种全自动稳健的图像拼接融合算法.中国图象图形学报：A辑.2004
[37]赵万金,龚声蓉,刘全,沈向军,刘纯平.一种用于图像拼接的图像序列自动排序算法.中国图象图形学报：A辑.2007
[38]段瑞玲,李庆祥,李玉和.图像边缘检测方法研究综述.光学技术.2005.31(3).415-419
[39]殷润民,李伯虎,柴旭东.自适应柱状全景图拼接.中国图象图形学报：A辑.2008
[40]罗钟铉,刘成明.灰度图像匹配的快速算法.计算机辅助设计与图形学学报.2005
[41]孙远,周刚慧,赵立初,施鹏飞.灰度图像匹配的快速算法.计算机辅助设计与图形学学报.2000
[42]彭文,童若峰,钱归平,董金祥.使用特征点与曲线配准医学图像.计算机辅助设计与图形学学报.2007
[43]周骥,石教英,赵友兵.图像特征点匹配的强壮算法.计算机辅助设计与图形学学报.2006
[44]李艳丽,向辉.稳健的球面全景图全自动生成算法.计算机辅助设计与图形学学报.2007
[45]倪国强,刘琼.多源图像配准技术分析与展望.光电工程.2004,31(9)：1～6