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An improved algorithm applied to electronic image stabilization based on SIFT

机译：一种基于SIFT的电子防抖改进算法

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摘要

Electronic image stabilization, a new generation of image stabilization technology, obtains distinct and stable image sequences by detecting inter-frame offset of image sequences and compensating by way of image processing. As a high-precision image processing algorithm, SIFT can be applied to object recognition and image matching, however, it is the extremely low processing speed that makes it not applicable in electronic image stabilization system which is strict with speed. Against the low speed defect of SIFT algorithm, this paper presents an improved SIFT algorithm aiming at electronic image stabilization system, which combines SEFT algorithm with Harris algorithm. Firstly, Harris operator is used to extract the corners out of two frames as feature points. Secondly, the gradients of each pixel within the 8x8 neighborhood of feature point are calculated. Then the feature point is described by the main direction. After that, the eigenvector descriptor of the feature point is calculated. Finally, matching is conducted between the feature points of current frame and reference frame. Compensation of the image is processed after the calculation of global motion vector from the local motion vector. According to the experimental results, the improved Harris-SIFT algorithm is less complex than the traditional SIFT algorithm as well as maintaining the same matching precision with faster processing speed. The algorithm can be applied in real time scenario. More than 80% match time can be saved for every two frames than the original algorithm. At the same time, the proposed algorithm is still valid when there are slightly rotations between the two matched frames. It is of important significance in electronic image stabilization technology.
机译：电子图像稳定技术是新一代的图像稳定技术，它通过检测图像序列的帧间偏移并通过图像处理进行补偿来获得独特而稳定的图像序列。作为一种高精度的图像处理算法，SIFT可以应用于物体识别和图像匹配，但是由于其极低的处理速度，使得SIFT不适用于速度要求严格的电子图像稳定系统。针对SIFT算法的低速缺陷，提出了一种针对电子图像稳定系统的改进SIFT算法，将SEFT算法与Harris算法相结合。首先，使用哈里斯算子从两个帧中提取角点作为特征点。其次，计算特征点在8x8邻域内的每个像素的梯度。然后，通过主方向描述特征点。之后，计算特征点的特征向量描述符。最后，在当前帧和参考帧的特征点之间进行匹配。在根据局部运动矢量计算出全局运动矢量之后，对图像进行补偿。根据实验结果，改进后的Harris-SIFT算法比传统的SIFT算法复杂度低，并且保持了相同的匹配精度和更快的处理速度。该算法可以应用于实时场景。与原始算法相比，每两帧可节省80％以上的匹配时间。同时，当两个匹配帧之间略微旋转时，所提出的算法仍然有效。在电子图像稳定技术中具有重要意义。

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  • 来源
  • 会议地点 Beijing(CN)
  • 作者

    Lu Dai; Xiaohua Liu; Yuejin Zhao; Liquan Dong; Bangze Zeng; Weiyu Liu;

  • 作者单位

    School of Optoelectronics, Beijing Institute of Technology, Beijing, 100081, China;

    School of Optoelectronics, Beijing Institute of Technology, Beijing, 100081, China;

    School of Optoelectronics, Beijing Institute of Technology, Beijing, 100081, China;

    School of Optoelectronics, Beijing Institute of Technology, Beijing, 100081, China;

    School of Optoelectronics, Beijing Institute of Technology, Beijing, 100081, China;

    School of Optoelectronics, Beijing Institute of Technology, Beijing, 100081, China;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Electronic image stabilization; SIFT; Harris corner;

    机译：电子防抖；筛;哈里斯角;

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