Image splicing algorithm

Image stitching algorithms combine multiple images in specific ways to form a larger composite image. Common image stitching algorithms include the following:

Overlap-based Stitching Algorithm

This method identifies overlapping regions across multiple images. By performing feature matching and blending operations on these overlapping areas, it stitches the images into a single composite.

Panoramic Stitching Algorithm

Typically employed to merge adjacent panoramic photographs or video frames into a continuous panorama, this algorithm generally encompasses feature point detection, feature matching, camera calibration, and projection transformation.

Image Stitching Algorithm Based on Plane Projection Transformation

This algorithm is commonly employed to stitch together multiple images captured at different angles or distances. It first identifies key points through feature detection and matching, then estimates camera poses using methods such as RANSAC, and finally merges images from varying perspectives via perspective transformation.

Image Stitching Algorithms Based on Depth Information

This approach employs depth information to assist image stitching. It incorporates depth data during feature point matching to further optimise the estimation of the single homography matrix.
The above outlines several common image stitching algorithms. In practical applications, multiple algorithms may be combined for use.

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