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.
Famous quotes containing the words image and/or analogy:
“All things uncomely and broken, all things worn out and old,
The cry of a child by the roadway, the creak of a lumbering cart,
The heavy steps of the ploughman, splashing the wintry mould,
Are wronging your image that blossoms a rose in the deeps of my heart.”
—William Butler Yeats (1865–1939)
“The whole of natural theology ... resolves itself into one simple, though somewhat ambiguous proposition, That the cause or causes of order in the universe probably bear some remote analogy to human intelligence.”
—David Hume (1711–1776)