Image stitching method based on characteristic point plane similarity

Abstract

The invention discloses an image stitching method based on characteristic point plane similarity, comprising first, respectively extracting characteristic points of two images to be stitched; matching the characteristic points to obtain characteristic point matching pairs; screening the characteristic point matching pairs based on plane similarity, the screening method including first randomly selecting a smallest sampling set; calculating the homography matrix of the smallest sampling set; calculating the residual error between each matching pair and a corresponding homography matrix to form a residual vector; and calculating the plane similarity between each two matching pairs according to a residual vector, and furthermore screening the matching pairs; calculating a transformational matrix according to screened matching sets, and transforming two images to be stitched into a same coordinate system; searching for an optimal stitching line; and fusing images according to the optimal stitching line to obtain an image stitching result. The method employs characteristic point matching pairs which are screened based on plane similarity to perform registering and stitching, and can improve image stitching accuracy and robustness.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and more specifically relates to an image splicing method based on feature point plane similarity. Background technique [0002] Image stitching is to synthesize a series of images with overlapping areas for the same scene into a wide-angle image. At present, there are mainly two ways to obtain high-resolution large-field images: one is to obtain them through professional image acquisition equipment such as wide-angle cameras; Large field of view images. The cost of obtaining panoramic images through professional equipment is usually too high to be widely used, so image stitching technology has become a research hotspot in computer vision, image processing and computer graphics. [0003] Image stitching can be roughly divided into two steps: image registration and image fusion. Image registration is to adopt a certain matching strategy to establish the transformation relationship betwe...

AI Technical Summary

Problems solved by technology

[0004] The traditional stitching technology based on feature points has certain requirements for the pose or scene of the camera during shooting: rotating and shooting images or shooting scenes at the same viewpoint can be approximated as planar scenes, while for images with parallax between different viewpoints, there is no It is difficult to achieve the ideal splicing effect

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