Performance evaluation of a novel sampling-based texture synthesis technique using different sized patches

We propose a novel sampling-based texture synthesis algorithm called Multipatch, which improves on the results of previous sampling-based algorithms by using patches of different size, and by minimizing global pasting errors. A key feature of the proposed algorithm is that it always converges to a local minimum. Multipatch, the patchwork algorithm, and Wei and Levoy’s multi-resolution texture synthesis algorithm, which is based on a tree-structured vector quantization method, are statistically analyzed and subjectively evaluated. The results of simulations show that the patchwork algorithm yields a perceptually acceptable texture in a shorter expected running time than the other two algorithms; however, Multipatch is the most efficient in terms of obtaining a good quality texture image.