Sparsely Sampled Field for Fast Gradient-Based Global Motion Estimation *

This paper presents a approach of sparsely sampled field for gradient-based global motion estimation (GME). For decreasing the computational complexity in gradient based GME, we propose an algorithm to obtain sparsely sampled field from the original image pixels firstly. Then, the low pass filter is employed for eliminating noise of original images. Finally, we propose a one-stage gradient based GME algorithm for global motion estimation. Simulation results show the comparisons of performance between our method and others.

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