Image registration and splicing method on the basis of Lucas-Kanade algorithm

Abstract

The present invention discloses an image registration and splicing method on the basis of a Lucas-Kanade algorithm. The method provided by the invention comprises: pretreatment of an original image, wherein unmatched parameters between two images are generated because of the differences such as shooting angles, shooting distances, shooting illumination and the like, and the pretreatment of images is carried out prior to the image registration; image registration, wherein the image registration is taken as a key step in the image splicing technology, the splicing quality of the images is largely determined by the precision of the image registration; and image fusion, wherein the objective of the image fusion is to convert registered images to be spliced to the same coordinate system for fusion of pixel levels through a coordinate conversion relation so as to more comprehensively display scene information. According to the invention, the problem is solved that the accuracy of a homography matrix estimation is low caused by few feature points and noise jamming, and an LK image aligning algorithm and the changed algorithm thereof are creatively provided for optimizing the homography matrix estimation. Through iteration optimization of a whole image, the mean square error of the image is minimized, and the accuracy of the homography matrix estimation is enhanced, so that the fusion effect of registration and splicing fusion of the image is improved.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an image registration and splicing method based on the Lucas-Kanade algorithm. Background technique [0002] Image mosaic (ImageMosaic) technology refers to the coordinate registration of multiple image sequences that are captured by the camera on the same scene and have overlapping areas with each other, and then form a wide viewing angle, distortion-free, New images with higher resolution and more image information. Image stitching technology has been applied in the field of remote sensing technology earlier, but it is limited to the shooting angle, and the camera can only capture a local area of ​​a certain scene. However, the scene images in local areas cannot fully display the scene information, so it is necessary to perform spatial registration, fusion and stitching of multiple local scene images taken under different imaging conditions to form a complete remote s...

AI Technical Summary

Problems solved by technology

In recent years, with the rapid development of information technology and electronic technology, fields such as medical images, aerial photography, and daily life needs require high-resolution images. If it is obtained by means of a panoramic camera or a wide-angle camera, the captured image Not only is the resolution limited, but image edges are often distorted, deformed, blurred, etc. In addition, due to the expensiveness and inoperability of these professional equipment, such methods cannot be popularized

Images