Hierarchical motion estimation algorithm using multiple candidates for frame rate up-conversion

Abstract

Motion estimation (ME) has the highest computational complexity in motion-compensated frame rate up-conversion (MC-FRUC). For the real-time implementation of FRUC, a fast ME algorithm is required. In this paper, a new hierarchical ME algorithm for MC-FRUC is proposed. It constructs an image pyramid by dividing the frame into several sub-images according to resolution, and performs ME at the top level to reduce complexity while improving accuracy by selecting multiple motion vector candidates. These candidates are refined at the lower levels, and the final motion vector is selected at the bottom level. Thus, the proposed algorithm obtains an average peak signal-to-noise ratio gain of upto 0.85 dB compared to conventional algorithms with lower computational complexity and yields interpolated images with better visual quality than other methods.