Sound textures are often noisy and chaotic. The processing of these sounds must be based on the statistics of its corresponding time-frequency representation. In order to transform sound tex- tures with existing mechanisms, a statistical model based on the STFT representation is favored. In this article, the relation be- tween statistics of a sound texture and its time-frequency repre- sentation is explored. We proposed an algorithm to extract and modify the statistical properties of a sound texture based on its STFT representation. It allows us to extract the statistical model of a sound texture and resynthesise the sound texture after modi- fications have been made. It could also be used to generate new samples of the sound texture from a given sample. The results of the experiment show that the algorithm is capable of generating high quality sounds from an extracted model. This result could serve as a basis for transformations like morphing or high-level control of sound textures.