Large viewing angle image matching method capable of combining region matching and point matching

The invention relates to a large viewing angle image matching method capable of combining region matching and point matching. The method comprises the steps of 1, inputting two images having large viewing angle changes; 2, carrying out region detection on the images by a maximally stable extremal region (MSER), and fitting an elliptic region by the mean value and the variance of the region; 3, normalizing the elliptic region into a circular region, and describing the circular region by a scale invariant feature transform (SIFT) descriptor; 4, adopting the nearest-neighbor than the next-nearest neighbor strategy, and selecting the initial region matching pair; 5, in the region matching pair, detecting feature points by an SIFT method; 6, describing the feature points to obtain an MSER-based 128-dimensional descriptor and a 2-dimensional space descriptor; 7, adopting a similarity strategy combined with the distance, and selecting an accurate matching point pair in the two images. The large viewing angle image matching method overcomes the defect that in the prior art, the description of the feature points does not have affine invariant and leaves out of consideration of space information, and can extract the matching point pair with higher accuracy so as to enable the matching point pair to be better used for image registration.