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

TL;DR

This paper introduces a fast, perception-based decolorization method for tone mapping that preserves luminance quality and enhances processing speed, suitable for various image applications.

Contribution

The paper presents a novel high-speed color decolorization technique based on human perception of color temperature, improving speed and luminance quality over existing methods.

Findings

Achieved 5.7x faster processing speed compared to previous algorithms.

Produced luminance comparable to state-of-the-art methods using objective metrics.

Demonstrated effective luminance distribution in tone mapping applications.

Abstract

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.