Method for automatically split-jointing wide-angle image

Abstract

A wide-angle image automatic joining method comprises: a step one of setting a moving speed of a wide-angle camera and an image collecting period; a step two of obtaining a superposition pixel width of two adjacent images; a step three of building an image non-linear aberration correcting mathematical model; a step four of creating an image data coordinate conversion relationship; a step five of calculating an aberration vector parameter and an outer parameter value; a step six of performing an inversion operation on the image with aberration to obtain the whole real image after correcting the non-linear aberration; a step seven of rapidly finding common characteristics of the two adjacent images in the superposition width of the images with corrected non-linear aberration; a step eight of realizing registration of the two images by perspective conversion; a step nine of joining the two registered images; a step ten of inosculating the joining position of the images based on a wavelet bicubic interpolation searching method. According to the invention, continuous inosculation and seamless join of the adjacent images can be automatically realized.

Description

technical field [0001] The present invention relates to a method in the technical field of image processing, in particular to a wide-angle image automatic splicing method. Background technique [0002] Image stitching is an important branch of computer vision, which seamlessly stitches more than two partially overlapping images to obtain images with higher resolution or wide viewing angles. Image stitching plays an important role in virtual reality, panorama production, medical imaging and other fields. Image stitching must complete two key processes of image registration and image fusion. Registration parameters such as image rotation and translation can be determined through image registration operations, and image fusion operations can make the composite images achieve natural transition and finally achieve seamless splicing. However, in practical applications, due to the differences in exposure of the digital images to be stitched, errors in image registration, morphol...

AI Technical Summary

Problems solved by technology

However, the shortcomings of this technology are: 1. It does not have the function of automatically correcting the deformation and distortion of the image; 2. The image is mapped to spherical coordinates after "vertical block" and "horizontal block", and then vertical It is more difficult to achieve accurate fusion and seamless stitching; 3. The basic method of image stitching is not suitable for automatic stitching of large and wide images

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