We study the relationship between local features and block matching in this paper. We show that the use of many features can greatly improve the block matching results by introducing several fast block matching algorithms. The first algorithm is pixel decimation-based. We show that pixels with larger gradient magnitude have larger motion compensation error. Therefore for pixel decimation-based fast block matching, it benefits to subsample the block by selecting pixels with the largest gradient magnitude. Such a gradient-assisted adaptive pixel selection strategy greatly outperforms two other subsampling procedures proposed in previous literature. Fast block matching can achieve the optimal performance obtained using full search. We present a family of such fast block matching algorithm using various local features, such as block mean and variance. Our algorithm reduces more than 80 percent computation, while achieving the same performance as the full search. This present a brand new approach toward fast block matching algorithm design.