  Local misalignment caused by global homography is a common issue in image
stitching task. Content-Preserving Warping (CPW) is a typical method to deal
with this issue, in which geometric and photometric constraints are imposed to
guide the warping process. One of its essential condition however, is colour
consistency, and an elusive goal in real world applications. In this paper, we
propose a Generalized Content-Preserving Warping (GCPW) method to alleviate
this problem. GCPW extends the original CPW by applying a colour model that
expresses the colour transformation between images locally, thus meeting the
photometric constraint requirements for effective image stitching. We combine
the photometric and geometric constraints and jointly estimate the colour
transformation and the warped mesh vertexes, simultaneously. We align images
locally with an optimal grid mesh generated by our GCPW method. Experiments on
both synthetic and real images demonstrate that our new method is robust to
colour variations, outperforming other state-of-the-art CPW-based image
stitching methods.
