Propagating adaptive-weighted vector median filter for motion-field smoothing

In the field of predictive video coding and format conversion, there is an increasing attention towards estimation of the true inter-frame motion. The restoration of motion vector field computed by 3-D RS is addressed and a propagating adaptive-weighted vector median (PAWVM) post-filter is proposed. This approach decomposes blocks to make a better estimation on object borders and propagates good vectors in the scanning direction. Furthermore, a hard-thresholding method is introduced into calculating vector weights to improve the propagating. By exploiting both the spatial correlation of the vector field and the matching error of candidate vectors, PAWVM makes a good balance between the smoothness of vector field and the prediction error, and the output vector field is more valid to reflect the true motion.     

一种平滑运动矢量场的扩散型矢量中值滤波器

提出了一种新的扩散型、自适应加权的矢量中值滤波器(PAWVM)，用于对三维递归搜索(3-D RS)块估计算法产生的矢量场进行调整。该滤波器将前一步估计中所采用的块分解为4个小块以精确地估计物体边界处的运动，并沿扫描方向扩散改进后的矢量；在考虑矢量场本身平滑性的同时，利用各候选矢量的匹配误差，通过一个无特征区域开关进一步控制各矢量权值的计算，提高了反映真实运动的矢量扩散的可能性。试验结果表明，该算法更好地平衡了运动矢量场的一致性和最终的预测误差，使矢量场更接近真实的物体运动。