A new patchwork simulation method with control of the local-mean histogram

We present a new stochastic simulation method that builds two-dimensional images by assembling together square image pieces called blocks. The blocks are taken from a reference image. Our method, called patchwork simulation method (PSM), enforces pattern continuity in the image. Moreover, PSM allows to control the image local-mean histogram. This histogram bin-frequencies can be set to user-defined target values that may differ from the reference image local-mean histogram. This flexibility enhances the PSM generality by enlarging the set of all possible simulations. The local-mean histogram control is achieved by adjusting suitably the transition probabilities that associate a new block to an existing neighborhood in the partly simulated image. For several types of synthetic images and one polymer blend image, we show that PSM reproduces faithfully the reference image visual appearance (i.e. patterns are correctly shaped) and that simulated images are statistically compatible with the target local-mean histogram. Moreover, we show that our method has the ability to produce simulations that respect conditional hard data as well as a target local-mean histogram.