A computationally efficient gradient search block matching algorithm for the motion estimation of image sequences

Abstract

A computationally efficient block matching algorithm is presented to perform motion estimation of image sequences. The algorithm evaluates an objective function for all neighbouring blocks and stops, when no further improvement can be achieved. The complexity of the algorithm is reduced significantly, as the objective function is calculated from the projections of the blocks along the horizontal and the vertical axis. Furthermore, the relationship between projections of the neighbouring blocks is utilized, so as to alleviate the need for fully calculating the projection vectors for each candidate block. The proposed algorithm is compared against the full search (FS), two-dimensional logarithmic search (2D LS), and block based gradient descent search (BBGDS), in terms of complexity and compression performance. Experimental results show that the proposed algorithm exhibits quite good performance at a significantly reduced computational complexity.