Video stabilization using kalman filter and phase correlation matching

  • Authors:

  • Ohyun Kwon;Jeongho Shin;Joonki Paik

  • Affiliations:

  • Image Processing and Intelligent Systems Laboratory, Department of Image Engineering, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, Seoul, Korea;Image Processing and Intelligent Systems Laboratory, Department of Image Engineering, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, Seoul, Korea;Image Processing and Intelligent Systems Laboratory, Department of Image Engineering, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, Seoul, Korea

  • Venue:
  • ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
  • Year:
  • 2005

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Abstract

A robust digital image stabilization algorithm is proposed using a Kalman filter-based global motion prediction and phase correlation-based motion correction. Global motion is basically estimated by adaptively averaging multiple local motions obtained by phase correlation. The distribution of phase correlation determines a local motion vector, and the global motion is obtained by suitably averaging multiple local motions. By accumulating the global motion at each frame, we can obtain the optimal motion vector that can stabilize the corresponding frame. The proposed algorithm is robust to camera vibration or unwanted movement regardless of object's movement. Experimental results show that the proposed digital image stabilization algorithm can efficiently remove camera jitter and provide continuously stabilized video.