An Image Matching Correction Method of Integrating Least Squares and Phase Correlation Using Window Series

Abstract

Matching is the knotty point in photogrammetry and computer vision. Aiming at inaccurate corresponding points after preliminary matching, this paper proposed an image matching correction method of integrating least squares and phase correlation using window series. The method firstly uses least squares and phase correlation matching to correct corresponding points in utilizing of window series, and simultaneously calculates correlation coefficients using windows of different size. And then the correlation coefficients are used as the index of evaluating whether the corresponding image points are accurate or not. So the matching results with the largest correlation coefficients are chosen as the final results. Based on experimental data-set 1 and data-set 2, the experimental results revealed that the use of window series can significantly improve the correction accuracy of preliminary matching results. And the proposed method can correct the corresponding points of preliminary matching effectively and greatly improve the overall matching accuracy, which is better than least squares matching or phase correlation matching using window series and fixed windows.