Stylized Black and White Images from Photographs David Mould University of Saskatchewan Kevin Grant University of Lethbridge Figure 1: Black and white image conversion. Left to right: original image; uni ed segmentation result; detail-oriented result; base+detail result. Abstract Halftoning algorithms attempt to match the tone of an input image despite lower color resolution in the output. However, in some artistic media and styles, tone matching is not at all the goal; rather, details are either portrayed sharply or omitted entirely. In this paper, we present an algorithm for abstracting arbitrary input images into black and white images. Our goal is to preserve details while as much as possible producing large regions of solid color in the output. We present two methods based on energy minimization, using loopy belief propagation and graph cuts, but it is dif cult to devise a single energy term that both suf ciently promotes coherence and adequately preserves details. We next propose a third algorithm separating these two concerns. Our third algorithm involves composing a base layer, consisting of large at-colored regions, with a detail layer, containing the small high-contrast details. The base layer is computed with energy minimization, while local adaptive thresholding
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Stylized black and white images from photographs
Mould, David; Grant, Kevin
Association for Computing Machinery — Jun 9, 2008
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