Aerial video registration combining optimal gradient filters and projective invariant

YI Meng; GUO Bao-long; YAN Chun-man

doi:10.3788/OPE.20122003.0651

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Aerial video registration combining optimal gradient filters and projective invariant

Article | 更新时间：2020-08-12

- Aerial video registration combining optimal gradient filters and projective invariant
- Optics and Precision Engineering Vol. 20, Issue 3, Pages: 651-660(2012)
- 作者机构：
  
  西安电子科技大学机电工程学院智能控制与图像工程研究所,陕西西安,710071
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20122003.0651
  CLC： TP391.41
- Received：10 June 2011，
  
  Revised：19 July 2011，
  
  Published Online：22 March 2012，
  
  Published：22 March 2012
- 稿件说明：
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易盟, 郭宝龙, 严春满. 结合优化梯度滤波与投影不变的航拍视频配准[J]. 光学精密工程, 2012,(3): 651-660

YI Meng, GUO Bao-long, YAN Chun-man. Aerial video registration combining optimal gradient filters and projective invariant[J]. Editorial Office of Optics and Precision Engineering, 2012,(3): 651-660
易盟, 郭宝龙, 严春满. 结合优化梯度滤波与投影不变的航拍视频配准[J]. 光学精密工程, 2012,(3): 651-660 DOI： 10.3788/OPE.20122003.0651.

YI Meng, GUO Bao-long, YAN Chun-man. Aerial video registration combining optimal gradient filters and projective invariant[J]. Editorial Office of Optics and Precision Engineering, 2012,(3): 651-660 DOI： 10.3788/OPE.20122003.0651.

摘要

考虑航拍视频配准中Harris检测的角点位置易发生偏移和产生伪角点以及匹配点精度不一致等问题

提出一种基于优化梯度滤波和投影不变的航拍视频配准算法。首先

提出一种基于优化梯度滤波的Harris检测器来实现角点的精确定位

并选择在尺度变化下局部区域最稳定的角点作为待配准点。然后

利用Delaunay三角网对待配准点进行初始匹配。最后

提出利用交比不变性方法提取精确度最高的少数匹配点

并对模型参数进行估计

完成视频帧间的配准。实验结果表明

利用提出的方法可实现帧间的精确配准

对分辨率为320 pixel240 pixel的8组航拍序列的平均几何保真度误差仅为0.869

并能有效提取地面运动目标。

Abstract

As the Harris detector can produce false and unstable corners

and obtained matching points have different accuracies in aerial video registration

an aerial video registration algorithm using optimal gradient filters and projective invariant was proposed. Firstly

a Harris detector based on optimal gradient filters was presented to determine the location of corners

and the locally most stable points were selected to be matching points. Then

the Delaunay triangulation was used to perform the initial matching. Finally

the most "useful" matching points that best satisfied the cross-ratio invariant were presented to estimate the geometry transformation and finish the image registration. Experiment results show that the proposed method by the optimal gradient filters and cross-ratio invariant can realize the registration between the frames

and the average geometric fidelity error is 0.869 for 8 sets of the unmanned video sequences with a resolution of 320 pixel?240 pixel. The method can capture moving objects effectively.

关键词

Keywords

references

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