视频图像运动估计中的一维块匹配算法

运动估计是视频图像压缩和视频图像修复等领域的基础问题,传统的块匹配法搜索质量较好,但搜索速度不够快.针对传统块匹配法搜索速度上的不足,提出一种快速的一维块匹配运动估计算法.首先对运动矢量正交分解,使用特殊权重系数矩阵对二维匹配块做降维处理,得到2组一维特征矩阵;然后选择一维三步搜索法作为搜索策略,最小绝对误差和准则作为匹配准则,使用2组一维特征矩阵搜索匹配运动矢量的2个分量;最后将分量组成完整的运动矢量.通过多组对比实验的结果表明,该算法在保证定量评价PSNR的前提下,显著提升运动估计的搜索速度,视频清晰度越高、匹配块像素尺寸越大,运动估计搜索速度提升越明显.

One-dimensional Block Matching Algorithm in Video Image Motion Estimation

Motion estimation is a basic problem in the fields of video image compression and video image restoration.The traditional block matching methods have good search quality,but the search speed is not fast enough.Aiming at the shortcomings of the search speed in the traditional block matching methods,we proposed a fast one-dimensional block matching motion estimation algorithm.Firstly,the motion vector is orthogonally decomposed,and the two-dimensional matching block is reduced by a special weight coefficient matrix to obtain two sets of one-dimensional feature matrices.Then the one-dimensional three step search method is selected as the search strategy.The sum of absolute differences criterion is used as the matching criterion.The two sets of one-dimensional feature matrices are used to search for the two components of the matching motion vector.Finally the two components are formed into a complete motion vector.The results of multiple sets of comparative experiments show that the search speed of motion estimation is significantly improved while the algorithm is guaranteed to quantitatively evaluate the PSNR.The higher the video definition and the larger the pixel size of the matching block,the better the algorithm can improve the search speed of motion estimation.