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.