Image: Impressionist Sunrise by Claude Monet, courtesy of. Our Color2Gray algorithm (Right) maps visible color changes to grayscale changes. Olsen Jack Tumblin Bruce Gooch Northwestern University Figure 1: A color image (Left) often reveals important visual details missing from a luminance-only image (Middle). CR Categories: I.4.3 : Enhancement Grayscale manipulations I.4.10 : Image Representations Multidimensional Keywords: non-photorealistic, image processing, color reduction, perceptually-based rendering Figure 2: Isoluminant changesĬolor2Gray: Salience-Preserving Color Removal Amy A. The Color2Gray results o er viewers salient information missing from previous grayscale image creation methods. The Color2Gray algorithm is a 3-step process: 1) convert RGB inputs to a perceptually uniform CIE L a b color space, 2) use chrominance and luminance di erences to create grayscale target di erences between nearby image pixels, and 3) solve an optimization problem designed to selectively modulate the grayscale representation as a function of the chroma variation of the source image. The algorithm introduced here reduces such losses by attempting to preserve the salient features of the color image. Abstract Visually important image features often disappear when color images are converted to grayscale. Tumblin, Jack Gooch, BruceĬolor2Gray: Salience-Preserving Color Removal Amy A. Color2Gray: salience-preserving color removal Color2Gray: salience-preserving color removal
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