Visually important image features often disappear when color images
are converted to grayscale. The algorithm introduced here reduces such
losses by attempting to preserve the salient features of the color
image. 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 differences to create grayscale target
differences 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 Color2Gray results offer viewers salient information missing from
previous grayscale image creation methods.
