| 引用本文: | 刘晓春,于起峰,雷志辉,等.机载平台野外立体场景弱小变化目标检测.[J].国防科技大学学报,2012,34(6):130-135.[点击复制] |
| LIU Xiaochun,YU Qifeng,LEI Zhihui,et al.Dim changing target detection of outside stereo scene for airborne platform[J].Journal of National University of Defense Technology,2012,34(6):130-135[点击复制] |
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| 机载平台野外立体场景弱小变化目标检测 |
| 刘晓春1,2, 于起峰1,2, 雷志辉1,2, 侯旺1,2 |
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(1.国防科技大学 航天与材料工程学院，湖南 长沙 410073;2.
2.摄影测量与视觉导航湖南省重点实验室，湖南 长沙 410073)
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| 摘要: |
| 提出了一种针对机载序列图像的野外立体场景弱小变化目标检测新方法。为了补偿平台运动，提出了一种级联图像配准模式，即首先通过生物视觉方法对待检图像进行快速粗配准，然后通过不变系数最小二乘匹配进行精配准；为了补偿图像间的灰度变化，提出了直方图一致性变换方法，该方法不仅可以处理线性灰度变化而且可以处理非线性灰度变化；为了弱化场景立体效应影响，提出分子区的方法，即通过将图像划分为若干子区，各对应子区独立求解仿射参数，使得待检图像不同位置子区可以对应不同几何变换参数。光电吊舱真实图像变化检测实验，证明了文章方法的正确性和有效性。 |
| 关键词: 变化检测 目标检测 立体效应 图像配准 最小二乘匹配 生物视觉 |
| DOI： |
| 投稿日期：2012-05-10 |
| 基金项目: |
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| Dim changing target detection of outside stereo scene for airborne platform |
| LIU Xiaochun1,2, YU Qifeng1,2, LEI Zhihui1,2, HOU Wang1,2 |
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(1.College of Aerospace and Materials Engineering, National University of Defense Technology, Changsha 410073, China;2.
2.Hunan Key Laboratory of Videometrics and Vision Navigation, Changsha 410073, China)
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| Abstract: |
| We present a new method to detect the dim changing target for the image sequence of outside stereo scene obtained from the airborne camera. In order to compensate for the movement of the platform, a cascading image registration mode is proposed, which firstly uses the biological vision method to register the images to be detected coarsely and fast, and which then uses least square match based on invariant coefficient to register the images accurately. In order to compensate for the gray-scale changes between the images, a new histogram similarity transformation is proposed, which is ?able to handle not only linear gray-scale changes but also nonlinear gray-scale changes. In order to reduce the stereo effect, a sub-region division method is proposed, which divides an image into several sub-regions, and then calculates the affine transformation parameters for each corresponding sub-regions independently. Using this scheme, we can make sure that different sub-regions correspond to different geometric transformation parameters. Experimental results using many real images obtained from electro-optic pods clearly demonstrate the correctness and validity of the method. |
| Keywords: change detection target detection stereo effect image registration least square matching biological vision |
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