Mathematical Models for Texture Image Synthesis
Abstract
In this talk, I will present several mathematical models for the problem of texture image synthesis. This problem consists in generating new images from a single exemplar image. Two main classes of models will be considered. The first one is the “copy-and-paste” type, and can be formalized using Markov chains. The second one is of a statistical nature: it consists in computing a set of statistics on the exemplar image and then generating new images that have these statistics. I will focus in particular on this latter approach, emphasizing models based on constrained maximum entropy distributions.