Two-step motion estimation algorithm using low-resolution quantization

We propose a new motion estimation algorithm using low-resolution quantization. The proposed algorithm reduces both performance degradation and computational cost by matching at every search position with a low bit resolution image. It consists of two steps: the low resolution search that generates the candidate motion vectors and the full-resolution search that finds the best motion vector in the candidates from the low-resolution search. Simulation results show that the PSNR of the proposed algorithm is superior to that of the 4:1 alternate subsampling algorithm and the one-dimensional full search algorithm with less computational cost. The PSNR degradation of the proposed algorithm with respect to the full search algorithm is less than 0.12 dB with 1/17.7 computational cost