Adapting the Sample Size in Texture Synthesis

Starting from a sample of a given size, texture synthesis algorithms are used to create larger texture images. A good algorithm produces synthesized textures that are pixelwise different but perceptually indistinguishable from the original image. The sample image should be chosen ensuring that it contains a number of pattern repetitions sufficient to produce valuable synthesis results. Since textures can be characterized by patterns of different dimensions, this must be done in an adaptive way. In this article, we propose a method that automatically adapts the sample size for natural textures synthesis, according to the different patterns dimensions. The method is based on the measure of the spatial dependence between the texture pixel values. This measure is used to estimate the size of the smallest texture window that is still perceived as texture by human observers. The sample size is determined from this measure by applying a multiplicative factor that depends on the algorithm used for synthesis. We perform a simple subjective experiment to estimate this factor for three different synthesis algorithms. We show that the measure of spatial dependence based on the correlation between pixels performs well when it is used to adapt the sample size