A matching method of underwater panoramic image based on ORB-GMS.

In order to expand the application range of underwater panoramic images, ensure the image matching robustness and effect, and improve the matching accuracy of underwater panoramic image, a matching method of underwater panoramic image based on ORB-GMS is proposed. After noise reduction processing of underwater panoramic images by wavelet thresholding method, the ORB algorithm is used to obtain feature point descriptions of underwater panoramic images after noise reduction by scale space construction, feature point detection and extraction, and descriptor construction. The feature points of underwater panoramic image extracted and described by the ORB algorithm are meshed using the GMS algorithm, and the results of the meshing are used as the neighborhood support estimates. Based on the grid motion, the statistical neighborhood support estimator is used to distinguish the correct matching points from the incorrect ones to complete the underwater panoramic image matching. The experimental results show that the proposed method for underwater panoramic image matching produces more matching points, more number of interior points, larger interior point ratio and less matching time consumption; it can effectively improve the matching accuracy of underwater panoramic images processed by scaling size, changing light and dark, and rotating angle transformation. [ABSTRACT FROM AUTHOR]