基于子块均值的快速块匹配算法  

Fast block matching algorithm based on subblock mean

作　　者：郭丽[1] 孙兴华[1] 杨静宇[1] 

机构地区：[1]南京理工大学计算机科学与技术学院,江苏南京210094

出　　处：《计算机应用》2006年第7期1595-1597,共3页journal of Computer Applications

摘　　要：根据积分图像对匹配误差函数进行变形,提出了一种新的局部匹配误差函数———基于子块均值的匹配误差函数。实验表明,基于子块均值的匹配误差函数与完全匹配误差函数相比具有相当的运动估算质量和更快的运动估算速度,与基于子抽样的匹配误差函数相比同时具有更优的运动估算质量和速度。子块划分的恒常性,也保证了基于子块均值的匹配误差函数对于不同的匹配图像所消耗的时间大致相同,非常适合于实时视频压缩等应用。Integral image as an intermediate image representation can be used to calculate the sum of gray level in rectangle quickly. A novel partial matching error function was presented based on sub block mean. Experiments show that the matching error function based on subblock mean is superior to beth the full matching error function and the matching error function based on sub -sampling in terms of the motion estimation quality and speed. The matching error function based on subblock mean with the constant subblock division costs almost the same time to different matching images, which is very suitable for the real-time applications such as video compression.

关 键 词：块匹配 积分图像 子块均值 匹配误差函数 峰值信噪比 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]