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Floyd–Steinberg dithering is an image dithering algorithm first published in 1976 by Robert W. Floyd and Louis Steinberg. It is commonly used by image manipulation software. It is commonly used by image manipulation software.
The same algorithms may be applied to each of the red, green, and blue (or cyan, magenta, yellow, black) channels of a color image to achieve a color effect on printers such as color laser printers that can only print single color values.
Ordered dithering is any image dithering algorithm which uses a pre-set threshold map tiled across an image. It is commonly used to display a continuous image on a display of smaller color depth . For example, Microsoft Windows uses it in 16-color graphics modes.
Atkinson dithering is a variant of Floyd–Steinberg dithering designed by Bill Atkinson at Apple Computer, and used in the original Macintosh computer. Implementation [ edit ]
The first printed photo using a halftone in a Canadian periodical, October 30, 1869 A multicolor postcard (1899) printed from hand-made halftone plates. While there were earlier mechanical printing processes that could imitate the tone and subtle details of a photograph, most notably the Woodburytype, expense and practicality prohibited their being used in mass commercial printing that used ...
The term dither was published in books on analog computation and hydraulically controlled guns shortly after World War II. [1] [2] [nb 1] Though he did not use the term dither, the concept of dithering to reduce quantization patterns was first applied by Lawrence G. Roberts [4] in his 1961 MIT master's thesis [5] and 1962 article. [6]
Adding an appropriate amount of dither during quantization prevents determinable errors correlated to the signal. If dither is not used then noise shaping effectively functions merely as distortion shaping — pushing the distortion energy around to different frequency bands, but it is still distortion. If dither is added to the process as
The algorithm, known as variable-pixel linear reconstruction, or informally as "Drizzle", preserves photometry and resolution, can weight input images according to the statistical significance of each pixel, and removes the effects of geometric distortion on both image shape and photometry. In addition, it is possible to use drizzling to ...