  Decolorization is the process to convert a color image or video to its
grayscale version, and it has received great attention in recent years. An
ideal decolorization algorithm should preserve the original color contrast as
much as possible. Meanwhile, it should provide the final decolorized result as
fast as possible. However, most of the current methods are suffering from
either unsatisfied color information preservation or high computational cost,
limiting their application value. In this paper, a simple but effective
technique is proposed for real-time decolorization. Based on the typical
rgb2gray() color conversion model, which produces a grayscale image by linearly
combining R, G, and B channels, we propose a dominant color hypothesis and a
corresponding distance measurement metric to evaluate the quality of grayscale
conversion. The local optimum scheme provides several "good" candidates in a
confidence interval, from which the "best" result can be extracted.
Experimental results demonstrate that remarkable simplicity of the proposed
method facilitates the process of high resolution images and videos in
real-time using a common CPU.
