基于局部不变特征的实时精确景象匹配算法研究
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摘要
本文开展了景象匹配辅助导航系统中基于局部不变特征的景象匹配算法研究,并通过建立仿真平台对提出的理论、算法和方案进行了验证。
在实际应用过程中,图像可能受到噪声、背景的干扰,也可能发生视角、光照、尺度、平移、旋转等变化,如何选择合理的图像匹配算法,使之满足景象匹配辅助导航系统的要求,即精确性、实时性、鲁棒性,是景象匹配算法的核心所在。考虑到采用部分Hausdorff距离度量进行图像匹配定位,匹配精度有限,速度较慢,抗旋转和抗噪声能力差,且难以精确确定图像之间的旋转变换参数,为此,本文通过引入图像局部不变特征并应用于景象匹配辅助导航中,可以有效克服部分Hausdorff距离度量上的不足,从而大大提高图像匹配算法性能。
SIFT(Scale Invariant Feature Transform)特征不仅具有良好的表征性能,而且在视角、尺度、旋转变化下保持不变。本文针对图像间存在较大几何畸变的情况,以SIFT特征为基础,提出并系统地阐述了基于SIFT特征的惯性/图形组合导航用景象匹配算法,该算法利用SIFT特征点实现特征匹配,提高了图像匹配精度、速度、稳定性和鲁棒性。
针对SAR图像受到几何畸变和严重斑点噪声影响下的景象匹配问题,本文引入了SURF(Speeded-Up Robust Features)算法来进行景象匹配辅助导航。SURF在重复性、独特性、鲁棒性、计算时间等方面相当或超过了现有算子,本文以此为基础,提出了一种鲁棒精确的图像匹配算法。通过大量仿真实验分析,验证了SURF算法在SAR/INS组合导航系统中具有良好的应用效果。
考虑到SIFT和SURF算法存在一定的误差,获得的特征点位置存在扭曲变化,本文利用RANSAC算法过滤掉错误和低精度的匹配点,并对提取出的特征点对进行最小二乘算法拟合,获取航向和位置偏差信息。
本文还结合工程实际应用情况,设计了景象匹配辅助导航系统仿真平台,该仿真平台以本文研究的图像匹配算法输出为信息来源,进行组合导航系统的误差修正,从而有效验证了所提出的算法的有效性。
The scene matching algorithm in the inertial integrated navigation system based on image local features is studied in this dissertation. Moreover, the theories, algorithms and ideas are verified through simulation platform and experiments.
It is important that image matching algorithm should be satisfy the demands of scene matching aided navigation system, that is precision, real-time and robust, and also should be robust to occlusion, background clutter and noise, invariant to various image transformations due to translation, rotation, scale, affine deformation, difference in illumination, object movement, and change in viewpoint. In consideration of the part Hausdorff distance as the similarity measuring to images match and localize, matching accuracy is limited, the speed is relatively slow, ability of rotation and noise resistance are poor, and difficult for getting the precision rotation transform parameters between images. So the local invariant feature is applied to scene matching aided navigation system.
SIFT(Scale Invariant Feature Transform) features are highly distinctive and invariant to various image transformations due to rotation, scale, and change in viewpoint. In the paper, we propose the scene matching algorithm based on SIFT features for inertial integrated navigation. We using SIFT features and feature matching algorithm, gives a reliable and fast image matching algorithm. This algorithm can improve the accuracy, real-time, and stability of the scene matching aided navigation system.
For the scene matching problem of SAR images by the geometric distortion and under the influence of serious speckle noise, the SURF(Speeded-Up Robust Features) algorithm of scene matching aided navigation is proposed. SURF approximates or even outperforms previously proposed schemes with respect to repeatability, distinctiveness, and robustness, yet can be computed and compared much faster. The experiment result demonstrates that the SURF in the SAR/INS integrated navigation system with good application.
At the same time, in the consideration of SIFT and SURF algorithms have certain errors, obtained the feature point position existence distortion change, the RANSAC algorithm is used to remove the false and low precision matching points, and the least square algorithm based on image points extraction is applied for getting both the aircraft position errors and course deviation.
Finally, based on engineering actual situation, using scene matching aided navigation system simulation platform, and the image matching algorithm proposed in this paper for the source of information are studied to amend the error. The simulation shows that the algorithm proposed in this dissertation is effective.
在实际应用过程中,图像可能受到噪声、背景的干扰,也可能发生视角、光照、尺度、平移、旋转等变化,如何选择合理的图像匹配算法,使之满足景象匹配辅助导航系统的要求,即精确性、实时性、鲁棒性,是景象匹配算法的核心所在。考虑到采用部分Hausdorff距离度量进行图像匹配定位,匹配精度有限,速度较慢,抗旋转和抗噪声能力差,且难以精确确定图像之间的旋转变换参数,为此,本文通过引入图像局部不变特征并应用于景象匹配辅助导航中,可以有效克服部分Hausdorff距离度量上的不足,从而大大提高图像匹配算法性能。
SIFT(Scale Invariant Feature Transform)特征不仅具有良好的表征性能,而且在视角、尺度、旋转变化下保持不变。本文针对图像间存在较大几何畸变的情况,以SIFT特征为基础,提出并系统地阐述了基于SIFT特征的惯性/图形组合导航用景象匹配算法,该算法利用SIFT特征点实现特征匹配,提高了图像匹配精度、速度、稳定性和鲁棒性。
针对SAR图像受到几何畸变和严重斑点噪声影响下的景象匹配问题,本文引入了SURF(Speeded-Up Robust Features)算法来进行景象匹配辅助导航。SURF在重复性、独特性、鲁棒性、计算时间等方面相当或超过了现有算子,本文以此为基础,提出了一种鲁棒精确的图像匹配算法。通过大量仿真实验分析,验证了SURF算法在SAR/INS组合导航系统中具有良好的应用效果。
考虑到SIFT和SURF算法存在一定的误差,获得的特征点位置存在扭曲变化,本文利用RANSAC算法过滤掉错误和低精度的匹配点,并对提取出的特征点对进行最小二乘算法拟合,获取航向和位置偏差信息。
本文还结合工程实际应用情况,设计了景象匹配辅助导航系统仿真平台,该仿真平台以本文研究的图像匹配算法输出为信息来源,进行组合导航系统的误差修正,从而有效验证了所提出的算法的有效性。
The scene matching algorithm in the inertial integrated navigation system based on image local features is studied in this dissertation. Moreover, the theories, algorithms and ideas are verified through simulation platform and experiments.
It is important that image matching algorithm should be satisfy the demands of scene matching aided navigation system, that is precision, real-time and robust, and also should be robust to occlusion, background clutter and noise, invariant to various image transformations due to translation, rotation, scale, affine deformation, difference in illumination, object movement, and change in viewpoint. In consideration of the part Hausdorff distance as the similarity measuring to images match and localize, matching accuracy is limited, the speed is relatively slow, ability of rotation and noise resistance are poor, and difficult for getting the precision rotation transform parameters between images. So the local invariant feature is applied to scene matching aided navigation system.
SIFT(Scale Invariant Feature Transform) features are highly distinctive and invariant to various image transformations due to rotation, scale, and change in viewpoint. In the paper, we propose the scene matching algorithm based on SIFT features for inertial integrated navigation. We using SIFT features and feature matching algorithm, gives a reliable and fast image matching algorithm. This algorithm can improve the accuracy, real-time, and stability of the scene matching aided navigation system.
For the scene matching problem of SAR images by the geometric distortion and under the influence of serious speckle noise, the SURF(Speeded-Up Robust Features) algorithm of scene matching aided navigation is proposed. SURF approximates or even outperforms previously proposed schemes with respect to repeatability, distinctiveness, and robustness, yet can be computed and compared much faster. The experiment result demonstrates that the SURF in the SAR/INS integrated navigation system with good application.
At the same time, in the consideration of SIFT and SURF algorithms have certain errors, obtained the feature point position existence distortion change, the RANSAC algorithm is used to remove the false and low precision matching points, and the least square algorithm based on image points extraction is applied for getting both the aircraft position errors and course deviation.
Finally, based on engineering actual situation, using scene matching aided navigation system simulation platform, and the image matching algorithm proposed in this paper for the source of information are studied to amend the error. The simulation shows that the algorithm proposed in this dissertation is effective.
引文
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[2]刘建业,赵伟,熊智,孙永荣.导航系统理论及应用.南京:南京航空航天大学出版社, 2005. 7
[3]陈哲.组合导航技术数字化与信息化的新进展.中国惯性技术学会第五届学术年会会议文集,桂林, 2003.12: 256-263
[4]赵伟.基于载波相位的GPS/惯性组合技术研究.南京:南京航空航天大学博士论文, 2002.1
[5]王瑞军.微型无人直升机组合导航系统研究与设计.南京:南京理工大学硕士论文, 2007.7
[6]刘家兴,陆明泉,崔晓伟,等.北斗无源定位的虚拟卫星算法.清华大学学报, 2009, 49(1): 49-52
[7]赵丽,刘建业,林雪原.双星定位系统改进方案与仿真研究.中国空间科学技术, 2004, 24(4): 18-23
[8]冷雪飞.基于图像特征的景象匹配辅助导航系统中的关键技术研究.南京:南京航空航天大学博士论文, 2007
[9]袁冬莉,闫建国,王新民,等.无人机组合导航系统信息融合方法研究.西北工业大学学报, 2006, 24(5): 558-561
[10] Blacknell D. Statistical target behaviour in SAR images. Radar, Sonar and Navigation, IEE Proceedings. 2000.6:143-148
[11] Ronald G.Caves, Peter J.Harley, Shaun Quegan. Matching map features to synthetic aperture radar (SAR) images Using Template Matching.IEEE Transactions on Geoscience and Remote sensing, 1992.7,30(4):680-685
[12] Hui Li, B.S.Manjunath, Sanjit K.Mitra. A contour-based approach to multisensor image registration. IEEE Transactions on image processing, 1995.3, 4(3):320-334
[13]杨莉.捷联惯性导航系统/合成孔径雷达双向信息融合技术的研究.南京航空航天大学博士论文, 2000
[14]廖明生.由INSAR影像高精度自动生成干涉图的关键技术研究.武汉:武汉大学博士论文, 2000
[15] Kirk JC,Jr. Digital synthetic aperture radar technology.IEEE International Radar ConferenceRecord,1975,2(1):482-487
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