A Subpixel Motion Estimation Approach Based on the Phase Correlation

Image registration is crucial in various image fusion tasks, like super-resolution. For the success of super-resolution reconstruction, it is essential to find out high accurate subpixel motion estimation between the input images sequence. This paper proposes a frequency domain-based motion estimation algorithm for the under-sampled infrared images. The proposed algorithm which only considers pure translational motion is based on the phase-only correlation. Due to the discrete Fourier transform and subpixel displacement, the signal peak is not always concentrate in the integer coordinates. Thus, the signals adjacent to peak are utilized to estimate aliasing influence. Excellent results are obtained for subpixel translation estimation. The algorithm is also compared to other algorithms, and the analyses show that this algorithm is more robust and accurate.