Image Mosaic Based on Phase Correlation and Harris Operator

In order to improve the insufficiency of harris corner, we present an auto-adjusted algorithm of image size based on phase-correlation. First, we detect the zoom relationship and translation co-efficiency between the images and modulate the unregistrated image’s scale to the same level as the original image. We obtain the Region of Interest (ROI) according to the translation parameter and then pre-treat the images and mark the interest points in the area by using improved harris corner operator. Secondly, we adopt Normalized Cross-Correlation (NCC) to wipe out the mismatched points preliminary after edging process, and get the final precise transformation matrix through Least Medium Square (LMedS) method. At last, we use method of weighted average to obtain a smooth mosaic image. The experimental results have shown that the setting of ROI and handling of the edge could cut the time down to about only half of the time consuming compared to SIFT; Besides, the scale difference between the images could enlarge from 1.8 to 4.7 and can eventually obtain a clear and stable mosaic result.