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Abstract
This paper proposes two
variants of a simple but efficient algorithm for structure-preserving
halftoning. Our algorithm extends Floyd-Steinberg error diffusion; the goal
of our extension is not only to produce good tone similarity but also to
preserve structure and especially contrast, motivated by our intuition that
human perception is sensitive to contrast. By enhancing contrast we attempt
to preserve and enhance structure also.
Our basic algorithm employs an adaptive, contrast-aware mask. To enhance
contrast, darker pixels should be more likely to be chosen as black pixels
while lighter pixels should be more likely to be set as white. Therefore,
when the positive error is diffused to nearby pixels in a mask, the dark
pixels absorb less error and the light pixels absorb more. Conversely,
negative error is distributed preferentially to dark pixels. We also propose
using a mask with values that drop off steeply from the centre, intended to
promote good spatial distribution. It is a very fast method whose speed
mainly depends on the size of the mask. But this method suffers from
distracting patterns.
We then propose a variant on the basic idea which overcomes the first
algorithm¡¯s shortcomings while maintaining its
advantages through a priority-aware scheme. Rather than proceeding in random
or raster order, we sort the image first; each pixel is assigned a priority
based on its up-to-date distance to black or to white, and pixels with
extreme intensities are processed earlier. Since we use the same mask
strategy as before, we promote good spatial distribution and high contrast.
We use tone similarity, structure similarity, and contrast similarity to
validate our algorithm. Comparisons with recent structure-aware algorithms
show that our method gives better results without sacrificing speed.
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Paper
(PDF, 2.22M)
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BibTex:
@article
{Li:2010:CAHalftoning,
author = {Li, Hua and Mould, David},
title = {Contrast-aware Halftoning},
journal = {Computer Graphics Forum},
volume = {29},
number = {2},
publisher = {Blackwell Publishing Ltd},
issn = {1467-8659},
url = {http://dx.doi.org/10.1111/j.1467-8659.2009.01596.x},
doi = {10.1111/j.1467-8659.2009.01596.x},
pages = {273--280},
keywords = {I.3.3 [Computer Graphics]: Picture/Image
Generation:Digitizing and scanning},
year = {2010},
}
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