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Face sketch synthesis using non-local means and patch-based seaming

This paper proposed a face sketch synthesis method by using non-local means (NL-Means), which takes the advantage of the non-local self-similarity of face photo and sketch patches. With a learning database of individuals described by one face photo and one face sketch, we assume that, for a given individual, the NL-Means coefficient of a given face photo patch is the same as its corresponding sketch patch. In order to handle the visible seam due to intensity difference of neighbor overlapping patches, we use patch based optimal seam to enforce the consistency of synthesized overlapping sketch patches. Experimental results on CUHK Face Sketch Database illustrate that our method has the advantage of easy implementation and much less required training samples, meanwhile our method can achieve fairly competitive synthesis results.