H.264 video coding standard has a significant performance better than the other standards are the adoption of variable block sizes, multiple reference frames, and the consideration of rate distortion optimization within the codec. However, these features incur a considerable complexity in the encoder for motion estimation. As for the multiple reference frames motion estimation, the increased computation is in proportion to the number of searched reference frames. In this paper, a fast multiple frame reference frames selection method is proposed for H.264 video coding. The proposed algorithm can efficiently determine the best reference frame from the allowed five reference frames. As determine the number of reference frames to search the motion using the correlation of the different block between the block of current frame and that of previous frame, this scheme can efficiently reduce the computational cost while keeping the similar quality and bit-rate. Simulation results show that the speed of the proposed method is faster than that of the original scheme adapted in JVT reference software JM95 while keeping the similar video quality and bit-rate.

By a measure we mean a function µ from {0, 1}* (the set of all binary sequences) to real numbers such that µ(x)0 and µ({0, 1}*). A malign measure is a measure such that if an input x in {0, 1}n (the set of all binary sequences of length n) is selected with the probability µ(x)/µ ({0, 1}n) then the worst-case computation time tWOA (n) and the average-case computation time tav,µA(n) of an algorithm A for inputs of length n are functions of n of the same order for any algorithm A. Li and Vitányi found that measures that are known as a priori measures are malign. We prove that a priori" -ness and malignness are different in one strong sense.