Abstract:

To further improve the operation efficiency, correct matching rate and registration accuracy of image registration, an image registration algorithm based on dual tree complex wavelet transform and speeded up robust features (SURF) is proposed. Firstly, the standard image and the image to be registered are decomposed into the low and high frequency parts by dual tree complex wavelet transform. The selected corresponding low frequency parts serve as the input image of the SURF algorithm, to obtain the coarse matching results. Then the coarse matching point pairs are purified and the mismatching point pairs are eliminated by the random sample consensus (RANSAC) algorithm. Thus the problem of more mismatching point pairs caused by the SURF algorithm is solved. Meanwhile, the transform model parameters of the optimal matching are calculated. Finally, the geometric transformation of the image to be registered is performed according to the transform model parameters, the gray level is determined by bilinear interpolation, and the image registration is completed. A large number of experimental results show that the proposed algorithm has a higher calculation speed, correct matching rate and registration accuracy than the scale invariant feature transform (SIFT) algorithm and the SURF algorithm. It also performs better in resisting noise, rotation and brightness change.