JACIII Vol.28 No.3 pp. 655-667
doi: 10.20965/jaciii.2024.p0655

Research Paper:

Color-to-Gray Conversion Method Based on Chroma Difference

Shi Bao*,† ORCID Icon, Huixin Liu*, Lu Min*, Dongsheng Xu**, and Gao Le*

*School of Information Engineering, Inner Mongolia University of Technology
49 Aimin Street, Xincheng District, Hohhot, Inner Mongolia 010051, China

Corresponding author

**Inner Mongolia Electronic Information Vocational and Technical College
No.8 Suergan Street, Saihan District, Hohhot City, Inner Mongolia 010028, China

August 31, 2023
February 15, 2024
May 20, 2024
chroma difference, color-to-gray conversion, color distance, color grayscale

Most of the images encountered in daily life are color images, yet grayscale remains prevalent in many fields due to its reduced data size and simplified operations. When reducing the dimensions of a three-channel color image to a single-channel grayscale, a portion of the original color information is inevitably lost. To yield high-quality grayscale images, this study introduces a color-to-gray conversion method based on chroma difference. This method defines a novel color distance metric for color-to-grayscale conversion, incorporating pixel chromaticity differences alongside brightness variations. The discrepancy in gray pixel values in the output grayscale image effectively mirrors the overall differences among input color image pixels. Optimization is conducted using the conjugate gradient method, ensuring appropriate reflection of luminance information from the input image and chromaticity data from the original color image within the grayscale rendering. Experimental validation confirms the efficacy of this approach. However, as the method accounts for all pixel pairs, it occasionally considers unnecessary pairs, leading to potential distortion in color differences between pixels and consequent inadequacies in chromaticity variation. To address this issue, a weighting factor is introduced, prioritizing color combinations with similar color differences. Experimental findings demonstrate that grayscale images produced using the proposed method outperform those generated by alternative approaches in preserving color differentials and retaining detailed features of the original image. The resulting output exhibits clear and natural outlines, as supported by both subjective and objective assessments.

Cite this article as:
S. Bao, H. Liu, L. Min, D. Xu, and G. Le, “Color-to-Gray Conversion Method Based on Chroma Difference,” J. Adv. Comput. Intell. Intell. Inform., Vol.28 No.3, pp. 655-667, 2024.
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Last updated on Jun. 03, 2024