  Grayscale images are fundamental to many image processing applications like
data compression, feature extraction, printing and tone mapping. However, some
image information is lost when converting from color to grayscale. In this
paper, we propose a light-weight 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 (like blue, green) to converge before
the warmer colors (like red, orange). This phenomena creates a perception of
warm colors "advancing" toward the eye, while 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)
channel. Our main contribution is threefold: First, we implement a high-speed
color processing method using exact pixel by pixel processing, and we report a
$5.7\times$ speed up when compared to other new algorithms. Second, our optimal
color conversion method produces luminance in images that are comparable to
other state of the art methods which we quantified using the objective metrics
(E-score and C2G-SSIM) and a subjective user study. Third, we demonstrate that
an effective luminance distribution can be achieved using our algorithm by
using global and local tone mapping applications.
