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兵工学报 ›› 2013, Vol. 34 ›› Issue (4): 406-411.doi: 10. 3969/ j. issn. 1000-1093. 2013. 04. 004

• 研究论文 • 上一篇    下一篇

一种基于分块灰度投影运动估计的视频稳像方法

吴浩1,2, 邓宏彬3   

  1. 1. 北京理工大学信息与电子学院, 北京100081;2. 北京理工大学计算机学院, 北京100081; 3. 北京理工大学机电学院, 北京100081
  • 上线日期:2013-07-23
  • 通讯作者: 吴浩 E-mail:wuhao@ bit. edu. cn
  • 作者简介:吴浩(1977—),男,讲师。

A Video Stabilization Method Based on Sub-block Gray Projection

WU Hao1,2, DENG Hong-bin3   

  1. 1. School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China; 2. School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China; 3. School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China
  • Online:2013-07-23
  • Contact: WU Hao E-mail:wuhao@ bit. edu. cn

摘要:

提出一种基于分块灰度投影运动估计的视频稳像方法,该方法首先对图像划分子区域, 依据灰度梯度对子区域进行筛选,剔除容易导致错误运动估计的低对比度子区域,在减少运动估计运算量的同时提高了运动矢量估计的精度;然后对保留的子区域进行灰度投影及相关运算获得局部运动矢量,根据图像帧间运动模型由局部运动计算出图像的全局运动矢量;最后根据运动补偿矢量对图像进行补偿,以获得稳定的图像序列。分块灰度投影运动估计算法有效解决了投影法存在的前景局部运动影响全局运动估计精度,以及无法估计旋转运动问题。实验结果表明,相比于传统灰度投影算法,该运动估计算法提高了运动估计的准确性和实时性。

关键词: 信息处理技术, 视频稳像, 运动估计, 灰度投影算法

Abstract:

A video stabilization method based on sub-block gray projection algorithm is proposed. Firstly, each image is divided into sub-blocks which are filtered according to their gray gradients. After the sub- blocks of which gray gradients are lower than a threshold are removed, the calculation amount of projec- tion is reduced and the motion estimation accuracy is improved. Then gray projection is done in the re- mained sub-blocks, and the global motion vector is calculated according to the local motion vectors and the interframe motion model. Finally, the trembling image is compensated to stabilize the image sequence according to motion compensating vector. The problems of that the global motion estimation accuracy is reduced by the local motion and the rotation motion of camera could not be estimated by traditional gray projection algorithm are effectively resolved by the sub-block gray projection algorithm. The experiment results show that the algorithm is more accurate and efficient than the traditional gray projection algo- rithm.

Key words: information processing, video stabilization, motion estimation, gray projection algorithm

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