  This paper introduces minimal solvers that jointly solve for radial lens
undistortion and affine-rectification using local features extracted from the
image of coplanar translated and reflected scene texture, which is common in
man-made environments. The proposed solvers accommodate different types of
local features and sampling strategies, and three of the proposed variants
require just one feature correspondence. State-of-the-art techniques from
algebraic geometry are used to simplify the formulation of the solvers. The
generated solvers are stable, small and fast. Synthetic and real-image
experiments show that the proposed solvers have superior robustness to noise
compared to the state of the art. The solvers are integrated with an automated
system for rectifying imaged scene planes from coplanar repeated texture.
Accurate rectifications on challenging imagery taken with narrow to wide
field-of-view lenses demonstrate the applicability of the proposed solvers.
