The image splicing algorithm is to stitch together multiple images in a certain way to form a larger image. Common image splicing algorithms are as follows:
Overlapping area splicing algorithm
Find the overlapping areas in multiple images, and assemble multiple images into one by feature matching and mixing processing of the overlapping area.
Panoramic splicing algorithm
The Panoramic splicing algorithm is usually used to stitch together multiple adjacent panoramic photos or video frames into a continuous panorama. The algorithm usually includes steps such as feature point detection, feature matching, camera correction and projection transformation.
Image splicing algorithm based on plane projection transformation
This algorithm is usually used to stitch together multiple pictures acquired at different angles or distances. The algorithm first finds the key points through feature point detection and matching, and then estimates the camera pose by RANSAC and other methods. Finally, the perspective transformation is used to merge the images from different perspectives.
Image splicing algorithm based on depth information
This algorithm uses depth information to assist image stitching, considers depth information in feature point matching, and further optimizes the estimation of monostress matrix.
These are some common image splicing algorithms, which may be combined with a variety of algorithms in practice.