摘要
MVFAST算法是视频压缩中一种重要的运动估计算法,但其缺乏是对图像时域相关性的考虑会造成不恰当的运动类型划分。因此,针对这个问题提出一种改进的运动矢量场自适应运动估计算法。该算法基于MVFAST分级搜索的思想,通过优化运动强度的划分方法,引入相对运动类型的划分来对大运动块自适应地选择搜索模式,使用简单的搜索策略,自适应地提前结束搜索。实验结果表明,该改进算法与MVFAST算法相比,在图像质量稍有下降的前提下,具有搜索速度上的明显优势。
MVFAST video compression algorithm is an important motion estimation algorithm, but it lacks the consideration of time domain correlation of images. This will result in an inappropriate division of motion types. Therefore, an improved adaptive motion estimation algorithm for motion vector field is presented to solve the problem. The new algorithm based on classifiable search mode in MVFAST improves the classification of motion intensity, imports the relative motion intensity classification of fast moving block to adaptively choose search strategy, uses more simple search method, and finishes the search adaptively. The result of experiments proves that the improved algorithm can improve the search velocity obviously in comparison with MVFAST algorithm.
出处
《现代电子技术》
2010年第20期75-78,共4页
Modern Electronics Technique
关键词
视频压缩
运动估计
块匹配
搜索策略
video compression
motion estimation
block matching
search strategy
