Image analogies

In many contexts, painting and illustration have many advantages over photorealistic computer graphics, in aspects such as aesthetics, expression, and computational requirements.


the code could be downloaded here

Wikipedia: An “image analogy” is a method of creating an image filter automatically from training data. In an image analogy process, the transformation between two images A and A’ is “learned”. Later, given a different image B, it’s “analogy” image B’ can be generated based on the learned transformation. The image analogy method has been used to simulate many types of image filters:

  • Toy filters, such as blurring or “embossing.”
  • Texture synthesis from an example texture.
  • Super-resolution, inferring a high-resolution image from a low-resolutinon source.
  • Texture transfer, in which images are “texturized” with some arbitrary source texture.
  • Artistic filters, in which various drawing and painting styles, including oil, pastel, and pen-and-ink rendering, are synthesized based on scanned real-world examples.
  • Texture-by-numbers, in which realistic scenes, composed of a variety of textures, are created using a simple “painting” interface.
  • Image colorization, where color is automatically added to grayscale images.

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