高精度全景补偿电子稳像

针对摄像机拍摄目标过程中自身的随机抖动造成的视频序列不稳定,以及稳像补偿过程中边缘信息的丢失,提出了基于SURF（Speed-up Robust Feature）算法的全景电子稳像方法。首先,运用SURF算法提取当前帧图像和参考帧图像的兴趣点,将两幅图像的兴趣点进行匹配,建立两帧的对应关系。针对兴趣点数目较少及场景中部分区域特征相似的情况,引入了兴趣点位移一致性抑制策略,改进了RANSAC（RANdom SAmple Consensus）误匹配的剔除算法,使得运动矢量的精确度小于1 pixel。然后,判定参考帧的更新策略,获取平滑的运动变量。最后,进行运动补偿,运用图像镶嵌技术对丢失的边缘区域信息进行全景补偿,得到了高精度的全景稳像结果,实验得到的输出视频峰值信噪比（PSNR）提高了33.1%。

High precision digital image stabilization with full frame compensation

To overcome the instability of the video sequences caused by the undesirable shakes of a camera, and to reduce the missing of edge information in the process of compensation, a full-frame video stabilization system based on the Speed-Up Robust Feature（SURF） was proposed. Firstly, the SURF was employed to ex- tract the features in the images of the current and the reference frames and to match the features between the two images, so that the correspondence could be established. As a few features were extracted and the features of some areas in the scene were similar, a method of consistency restrain of the features＇ displacement was pro- posed to ameliorate the RANSAC. The motion vector precision is less than 1 pixel. Secondly, by determining the reference frame update strategy, the smoothed inter-frame global motion vector was obtained. Finally, mo- saic was used to implement the motion compensation, and the corresponding pixels of the reference frame were filled with a stabilized frame to compensate the unstable motion and to output a stabilized full frame video. The Peak Signal to Noise Ratio（PSNR） is improved by 33.1 percent.