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We introduce an example-based synthesis technique that extrapolates novel styles for a given input image. The technique is based on separating the style and content of image fragments. Given an image with a new style and content, it is first adaptively partitioned into fragments. Stitching together novel fragments produces a coherent image in a new style for a given content. The aggregate of synthesized fragments approximates a globally non-linear model with a set of locally linear models. We show the result of our method for various artistic, sketch, and texture filters and painterly styles applied to different image content classes.