Principle:Kornia Kornia Image Stitching
| Knowledge Sources | |
|---|---|
| Domains | Vision, Geometry, Image_Processing |
| Last Updated | 2026-02-09 15:00 GMT |
Overview
Technique of combining multiple overlapping images into a seamless panoramic composite through feature matching, homography estimation, and image warping.
Description
Image stitching creates panoramic images by:
- Detecting and matching features between overlapping image pairs.
- Estimating a homography (projective transformation) that maps one image's coordinate system to another's.
- Warping the source image into the reference frame using perspective warping.
- Blending the warped images to minimize visible seams.
The process extends to multiple images by iteratively stitching pairs from left to right. Quality depends on sufficient overlap between images, accurate feature matching, and robust homography estimation.
Usage
Use when creating panoramic images from multiple overlapping photographs. Requires images with significant overlap (typically 30–50%) and works best with planar scenes or distant subjects where the homography model is valid.
Theoretical Basis
Given feature matches (p1_i, p2_i) between two images, compute homography H such that:
p2_i ≈ H * p1_i
The warped image:
I_warped(x') = I_src(H^{-1} * x')
Blending combines warped and reference images:
I_out = blend(I_warped, I_ref, mask)
For N images, iterate:
result = stitch(result, img_i) for i in 2..N