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Grayscale images are fundamental to many image processing applications likedata compression, feature extraction, printing and tone mapping. However, someimage information is lost when converting from color to grayscale. In thispaper, we propose a light-weight and high-speed image decolorization methodbased on human perception of color temperatures. Chromatic aberration resultsfrom differential refraction of light depending on its wavelength. It causessome rays corresponding to cooler colors (like blue, green) to converge beforethe warmer colors (like red, orange). This phenomena creates a perception ofwarm colors "advancing" toward the eye, while the cool colors to be "receding"away. In this proposed color to gray conversion model, we implement a weightedblending function to combine red (perceived warm) and blue (perceived cool)channel. Our main contribution is threefold: First, we implement a high-speedcolor 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 optimalcolor conversion method produces luminance in images that are comparable toother 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 thatan effective luminance distribution can be achieved using our algorithm byusing global and local tone mapping applications.

A color temperature-based high-speed decolorization: an empirical approach for tone mapping applications