In this paper, subpixel shift estimation method using phase correlation with local region is proposed for registration of
noisy images. Commonly, phase correlation based on the Fourier shift property is used to estimate the shift between
images. Subpixel shift of images can be estimated by the analysis for the phase correlation of downsampled images.
However, in case of images with noise or aliasing artifacts, the error in estimation is increased. Thus, we consider a
small region in a corner of an image instead of the whole, because flat regions with noise and regions with aliasing
induce the error of estimation. In addition, to improve accuracy, the local regions are inversely shifted by varying the
subpixel shift values, and obtaining the peak value of phase correlation between the images. Then, the subpixel shift
value corresponding to the maximum of the peak values is selected. Real-time implementation of this process is possible
because only a local region is used, thereby reducing the process time. In experiments, the proposed method is
compared with conventional methods using several fitting functions, and it is applied for the task of super resolution
imaging. The proposed method shows higher accuracy in registration than other methods, also, edge-sharpness in superresolved
images is improved.