Fixed matrix displays require digital interpolation algorithms to adapt the input spatial format to the output matrix. Interpolation techniques usually employed for this purpose exploit linear kernels designed to preserve the spectral content (anti aliasing), but this generates smooth edges, which result in unpleasant text images where sharpness is essential. By contrast, interpolation kernels designed to preserve sharpness introduce geometrical distortions in the scaled text (e.g. nearest neighbor interpolation). This paper describes an interpolation algorithm which, compared to linear techniques, aims to increase the sharpness of interpolated text while preserving its geometrical regularity. The basic idea is to differentiate the processing for text and non-text pixels. Firstly, a binary text map is built. By using morphological constraints it is possible to form a similar text map in the output domain that preserves the general text regularity. Finally, output text pixel positions are used to control a nonlinear interpolator (based on the Warped Distance approach) that is able to generate both step and gradual luminance profiles, thus enabling the algorithm to locally change its behavior. A general sharpness control is provided as well, which permits to range from a two-level text (maximum sharpness) to a smoother output image (traditional linear interpolation).