Binocular camera-based panoramic image splicing method

Abstract

The invention provides a binocular camera-based panoramic image splicing method. According to the method, a binocular camera is arranged at a certain point of view in the space, the binocular camera completes photographing for once and obtains two fisheye images; a traditional algorithm is improved according to the defect of insufficient distortion correction capacity of a latitude-longitude correction method in a horizontal direction; corrected images are projected into the same coordinate system through using a spherical surface orthographic projection method, so that the fast correction of the fisheye images can be realized; feature points in an overlapping area of the two projected images are extracted based on an SIFT feature point detection method; the search strategy of a K-D tree is adopted to search Euclidean nearest neighbor distances of the feature points, so that feature point matching can be performed; an RANSAC (random sample consensus) algorithm is used to perform de-noising on the feature points and eliminate mismatching points, so that image splicing can be completed; and a linear fusion method is adopted to fuse spliced images, and therefore, color and scene change bluntness in an image transition area can be avoided.

Description

technical field [0001] The invention belongs to the field of digital image processing, and relates to a panoramic image stitching method, in particular to a binocular camera-based panoramic image stitching method. Background technique [0002] With the development of science and technology, the application of panoramic vision is more and more extensive, including applications in meteorology, medical treatment, security monitoring, detection technology and so on. The process of stitching multiple images into a panoramic image is not only complicated and inefficient, but also has low applicability in practical engineering applications. [0003] The fisheye lens has a wider viewing angle than ordinary cameras. In order to simplify the model of the camera placement device for multi-directional shooting covering the panorama, the binocular camera obtains two fisheye images covering the panorama by shooting in opposite directions at the same time. After a series of The image proc...

AI Technical Summary

Problems solved by technology

[0007] The longitude and latitude correction algorithm is a typical representative of two-dimensional correction, with a small amount of calculation and a simple correction process. For the traditional longitude and latitude correction algorithm, the longitude and latitude on the spherical surface are mapped to correspond to the horizontal and vertical coordinates of the plane image, and the correction effect of the corrected image in the vertical direction It is better, but the arch distortion correction in the horizontal direction fails, and the problem of excessive center correction and insufficient edge correction occurs. In order to solve the defect of the traditional longitude and latitude correction method, a double longitude distortion correction method is proposed. Meridian and latitude are regarded as horizontal meridian and longitudinal meridian to map and correct the distorted image, which improves the correction accuracy

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