Quad-Tree Motion Estimation in the Frequency Domain Using Gradient Correlation

We propose a new motion estimation scheme particularly suitable for broadcast-quality digital video applications due to its performance-complexity characteristics. The proposed scheme is based on the principle of gradient correlation and its computational efficiency is due to the fact that it operates in the frequency domain. The scheme involves the quad-tree decomposition of a frame thus providing a better level of adaptation to scene contents compared to fixed block size approaches. Quad-tree decompositions are obtained by using the motion compensated prediction error to control the partition of a parent block to four children quadrants. The partition criterion is applied iteratively until a target number of motion vectors or a target level of motion compensated prediction error is achieved or, ultimately, until no more than a single motion component can be identified. The partition criterion also guarantees a monotonic decrease of the motion compensated prediction error with an increasing number of iterations making our scheme suitable for progressive transmission and embedded coding applications. Our results show that our scheme outperforms fixed block size phase correlation as well as quad-tree motion estimation based on phase correlation in terms of rate-distortion characteristics yielding smoother motion vector fields as well as more compressible motion-compensated prediction residuals.