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Lai Lijun, Xu Zhiyong, Zhang Xuyao. Improved gradient optical flow for digital image stabilization[J]. Infrared and Laser Engineering, 2016, 45(4): 428004-0428004(7). doi: 10.3788/IRLA201645.0428004
Citation: Lai Lijun, Xu Zhiyong, Zhang Xuyao. Improved gradient optical flow for digital image stabilization[J]. Infrared and Laser Engineering, 2016, 45(4): 428004-0428004(7). doi: 10.3788/IRLA201645.0428004
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Improved gradient optical flow for digital image stabilization

doi: 10.3788/IRLA201645.0428004
  • 1.

    Institute of Optics and Electronics,Chinese Academy of Sciences,Chengdu 610209,China

  • Received Date: 2015-08-11
  • Rev Recd Date: 2015-09-20
  • Publish Date: 2016-04-25
  • Traditional gradient optical flow has large motion estimation deviation with real value, thus cannot be directly applied to image stabilization system. In order to improve traditional gradient optical flow, a pyramid multi-resolution coarse-to-fine search strategy was incorporated into this algorithm. Firstly, computing area affine transform parameters were selected as the final transform parameters. Then, in the compensation period, error control propagation method was selected to obtain long term stabilized sequence. The experiment results show the improved method can detect severe complex jitter, and can achieve the rotating precision less than 0.09, translation precision less than 0.07, scaling precision less than 0.02, the compensation sequences' average PSNR raised 2.36 dB.
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    [2] Wang Zhiming, Xu Xiaogang. A survey on electronic image stabilization[J]. Journal of Image and Graphics, 2010, 15(3):470-480. (in Chinese)王志民, 徐晓刚. 电子稳像技术综述[J]. 中国图像图形学报, 2010,15(3):470-480.
    [3] Liu K X, Qian J, Yang R K. Block matching algorithm based on RANSAC algorithm[C]//2010 International Conference on IASP, 2010:400-405.
    [4] Zhong Ping. Application of improved representative point match algorithm in electronic image stabilization[J]. Optical Technique, 2005, 31(5):742-745. (in Chinese)钟平. 一种改进的代表点匹配算法在稳像技术中的应用[J]. 光学技术, 2005, 31(5):742-745.
    [5] Sanjeev Kumar, Haleh Azartash, Mainak Biswas. Real-time affine global motion estimation using phase correlation and its application for digital image stabilization[J]. IEEE Transactions on Image Processing, 2011, 20(12):3406-3418.
    [6] Qi Hong, Ren Hong, Tian Shaoqing, et al. An improved electronic image stabilization method based on gray projection[J]. Acta Scientiarum Naturalium Universitatis Sunyatseni, 2012, 2(5):44-49. (in Chinese)齐红, 任红娥, 田少卿, 等. 一种基于灰度投影的改进电子稳像方法[J]. 中山大学学报(自然科学版), 2012, 2(5):44-49.
    [7] Battiato S, Gallo G, Puglisi G, et al. SIFT features tracking for video stabilization[C]//IEEE International Conference on Image Analysis and Processing, 2007:825-830.
    [8] Lee K-Y, Yu Y, Chuang B-Y, et al. Video stabilization using robust feature trajectories[C]//IEEE 12th International Conference on Computer Vision, 2009:1394-1404.
    [9] Zhou Yajun, Tao Shengxiang, Zhang shu, et al. Image stabilization algorithm based on Harris[J]. Laser Infrared, 2009, 39(5):555-557. (in Chinese)周亚军, 陶声祥, 张舒, 等. 一种基于Harris角点特征的稳像算法[J]. 激光与红外, 2009, 39(5):555-557.
    [10] Chen Xiaolu, Dai Ming, Ge Ming, et al. Fast smoothing point-feature trajectories for digital image stabilization[J]. Infrared and Laser Engineering, 2014, 43(6):1988-1993. (in Chinese)陈晓露, 戴明, 葛明, 等. 快速平滑特征轨迹电子稳像[J]. 红外与激光工程, 2014, 43(6):1988-1993.
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Improved gradient optical flow for digital image stabilization

doi: 10.3788/IRLA201645.0428004
  • 1. Institute of Optics and Electronics,Chinese Academy of Sciences,Chengdu 610209,China
  • Received Date: 2015-08-11
  • Rev Recd Date: 2015-09-20
  • Publish Date: 2016-04-25

Abstract: Traditional gradient optical flow has large motion estimation deviation with real value, thus cannot be directly applied to image stabilization system. In order to improve traditional gradient optical flow, a pyramid multi-resolution coarse-to-fine search strategy was incorporated into this algorithm. Firstly, computing area affine transform parameters were selected as the final transform parameters. Then, in the compensation period, error control propagation method was selected to obtain long term stabilized sequence. The experiment results show the improved method can detect severe complex jitter, and can achieve the rotating precision less than 0.09, translation precision less than 0.07, scaling precision less than 0.02, the compensation sequences' average PSNR raised 2.36 dB.

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