An improved subpixel image registration algorithm based on singular value decomposition

doi:10.7523/j.issn.2095-6134.2019.01.014

Abstract

Abstract: Phase correlation method based on singular value decomposition (SVD) is a known subpixel image registration algorithm. However, when the translation between two images to be registered is large or there is high noise, the phase unwrapping results obtained using the integral method in the registration algorithm are often unreliable. In this work, an improved phase unwrapping algorithm is proposed based on the monotonic variation of linear phase. By comparing the consistency of the adjacent phase differences and the trend slopes, the algorithm determines whether to make corrections, so as to get the real phase. Experiments on real optical images show that the proposed method effectively corrects the results obtained using the integral method, and hence increases matching accuracy.

Key words: image registration, subpixel, singular value decomposition, phase unwrapping, integral method

CLC Number:

TP391.41

LING Cheng, GENG Xiurui, YANG Weitun, ZHAO Yongchao. An improved subpixel image registration algorithm based on singular value decomposition[J]. , 2019, 36(1): 101-108.

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