New Motion Estimation Algorithm and Its Block-Matching Criteria Using Low-Resolution Quantization

Abstract

We propose a new motion estimation algorithm and its block-matching criteria using low-resolution quantization. The proposed algorithm reduces both the huge computational cost of the full search algorithm and the performance degradation of the fast algorithms by matching the low-resolution images. Two search steps called the lowresolution search and the full-resolution search are employed. Simulation results show that the PSNR of the proposed algorithm is superior to those of the 4:1 alternate subsampling algorithm with less computational cost. Its computational cost is 1/38.1 of the full search algorithm.