# Quasi-homography warps in image stitching

## TL;DR

This paper introduces a quasi-homography warp for image stitching that balances perspective and projective distortions, resulting in more natural panoramas without additional parameters.

## Contribution

It proposes a novel, parameter-free warp formulation that effectively balances distortions, outperforming existing methods in urban scene stitching.

## Key findings

- Outperforms state-of-the-art warps like homography, AutoStitch, and SPHP in urban scenes.
- Receives higher user preference compared to homography and SPHP.
- Balances perspective and projective distortions effectively.

## Abstract

The naturalness of warps is gaining extensive attentions in image stitching. Recent warps such as SPHP and AANAP, use global similarity warps to mitigate projective distortion (which enlarges regions), however, they necessarily bring in perspective distortion (which generates inconsistencies). In this paper, we propose a novel quasi-homography warp, which effectively balances the perspective distortion against the projective distortion in the non-overlapping region to create a more natural-looking panorama. Our approach formulates the warp as the solution of a bivariate system, where perspective distortion and projective distortion are characterized as slope preservation and scale linearization respectively. Because our proposed warp only relies on a global homography, thus it is totally parameter-free. A comprehensive experiment shows that a quasi-homography warp outperforms some state-of-the-art warps in urban scenes, including homography, AutoStitch and SPHP. A user study demonstrates that it wins most users' favor, comparing to homography and SPHP.