Grayscale images are fundamental to many image processing applications, such as data compression, feature extraction, printing, and tone mapping. However, some image information is lost when converting from color to grayscale. We propose a lightweight and high-speed image decolorization method based on human perception of color temperatures. Chromatic aberration results from differential refraction of light depending on its wavelength. It causes some rays corresponding to cooler colors (such as blue, green) to converge before the warmer colors (such as red and orange). This phenomenon creates a perception of warm colors “advancing” toward the eye, whereas the cool colors to be “receding” away. In this proposed color-to-gray conversion model, we implement a weighted blending function to combine red (perceived warm) and blue (perceived cool) channels. Our main contribution is threefold. First, we implement a high-speed color processing method using exact pixel-by-pixel processing, and we report a 5.7  ×   speed up compared with other new algorithms. Second, our optimal color conversion method produces luminance in images that are comparable to other state-of-the-art methods that we quantified using the objective metrics (E-score and C2G-SSIM) and subjective user studies (decolorization and tone mapping). Third, we demonstrate that an effective luminance distribution can be achieved using our algorithm using global and local tone mapping applications.