一种快速、鲁棒的压缩视频光流场估计算法

该文针对视频运动特性的快速分析需求，提出了一种压缩域中的光流场估计算法。首先利用DCT变换后的两个AC系数估计出图像的空间偏导数，在此基础上再利用预测残差以及运动矢量对图像的时间偏导数进行估计。另外对编码过程中未进行前向运动预测的宏块特性进行了详细的分析，给出了这些宏块相对于前向参考帧的运动信息估计方法，并对时域不连续的图像块给出了一种修正的偏导数估计方法，以此解决遮挡、切换等现象。然后通过最小二乘法并结合图像的偏导数进行光流场估计。实验表明该方法在准确度上可以达到或超过像素域中的L-K估计方法，比起现有的压缩域估计方法也有一定提高，而在计算时间上相比像素域估计有了大幅度降低。

A Fast, Robust Optical Flow Estimation Method for Compressed Video

To analyze quickly the motion information of videos,a fast optical flow estimation algorithm for compressed domain is proposed.Firstly the spatial partial derivatives of image luminance are estimated by using two AC coefficients,and then the predictive residual errors and motion vectors of blocks are appended to estimate the temporal partial derivatives.In addition,after the detailed analysis of those macro-blocks that had no forward motion estimation,the motion information is given approximatively relative to their forward reference frames.And then,a amendatory partial derivative estimation is given for the inconsecutive image blocks when occlusion and cut had happened.Finally,optical flow estimation is performed based on the least square method and partial derivative estimation.Experiments indicated that this method can more accurately estimate the optical flow than the L-K method in pixel domain and the exist method in compressed domain.Moreover the proposed method can greatly reduce the compute time than the estimation in pixel domain.