We present a user-centered approach to image-based tex- ture synthesis. The synthesis uses a user-defined brush as generation primitive. This allows synthesis of textures at the texel level and further integration of the method into most of the existing digital image edition softwares. We treat texture images as probability density estimators from which new images with perceptually similar appearance and structure can be sampled. We model the input texture sample as a Markov Random Field and propose several al- gorithms based on the locality and stationarity principles assumed from the theory.
|Tijdschrift||ICGST International Journal on Graphics, Vision and Image Processing|
|Status||Published - 2005|