一种改进的完全搜索块匹配算法

Improved full-search block-matching algorithm

完全搜索块匹配算法是图像序列稳定中常用的运动估计方法,在传统的完全搜索块匹配算法中,在搜索区域中图像序列的当前帧和参考帧对应的像素对对匹配结果的贡献是完全一样的,这样使得算法的性能容易受到待稳定的图像序列中各种噪声的影响。针对这个不足,提出了一种改进的完全搜索块匹配算法。在新的匹配准则中,搜索区域中图像序列的当前帧和参考帧对应的像素对对匹配结果是否有贡献取决于它们灰度值之差的绝对值与预先设定的门限值进行大小比较的结果,对应的灰度值之差的绝对值不超过该门限值的像素对对匹配结果有贡献,而且贡献大小受到与像素对位置相关的加权处理,否则该像素对对匹配结果无贡献。实验结果证明了该算法的优越性。

The full-search block-matching (FSBM) algorithm is an ordinary motion estimation / method in image sequence stability. In traditional FSBM algorithm, every pair of pixels corresponding to the current and reference frame makes equal contribution to the matching result. Therefore, the performance of the traditional FSBM algorithm will tend to be influenced by various noise in the being stabilized image sequence. Aiming at the shortcoming, an improved FSBM algorithm is proposed. In the new matching rule, every pair of pixels is classified as matching pixel pair (set value as 1) or mismatching pixel pair (set value as 0). A threshold is selected to perform the above classification. The mismatching pixel pairs make no contribution to the result. Now the matching pixel pairs make equal contribution to the matching result as before, then multiply each by a weight that has relation with the position of the matching pixel pair and sum them up. The experiments show that this new method is promising.