Abstract: This paper proposed a motion-adaptive de-interlacing algorithm with high performance based on the analysis of the advantages and disadvantages of traditional de-interlacing algorithm for video surveillance systems. The algorithm divided the picture into static region and motion region on the basis of the motion state of interpolation points through 4-field motion detection which could detect the spatial-periodic pattern moving. Field insertion algorithm was exploited for interpolation of the static region. A modified edge-adaptive interpolation algorithm was used for the interpolation of the motion region which could increase the function of horizontal edge detection and enhance the level of consistency edge direction estimation. The proposed interpolation algorithm was implemented on DSP for experimental verification. The results show that the algorithm improves Peak Signal-to-Noise Ratio (PSNR) and Structural SIMilarity (SSIM) and restrains saw-tooth, interline flicker, motion virtual image and other adverse effects and gets bettter visual effects.

Key words: de-interlacing, motion detection, spatial-periodic pattern moving, edge-adaptive interpolation

摘要： 针对视频监控系统的去隔行问题，在分析了传统去隔行算法优缺点的基础上，提出了一种高性能的运动自适应去隔行算法。该算法通过可检测空间周期模式运动的4场运动检测方法对插值点运动状态进行判断，将图像分为静止区域和运动区域。静止区域的插值采用场合并算法；运功区域的插值采用改进型边沿自适应插值算法，增强了水平边沿检测功能并提升了一致性边沿方向的估计水平。DSP实验结果表明，提出的算法可提高图像的峰值信噪比(PSNR)和结构相似度(SSIM)，有效抑制锯齿化、行间闪烁和运动虚像等不良效应，获得良好的视觉效果

关键词: 去隔行, 运动检测, 空间周期模式运动, 边沿自适应插值