Abstract
In this paper, we study how to convert a color image to a grayscale image, and consider an effective contrast maximization method for color-to-grayscale conversion. Our method is based on the combination of red, green and blue channels pixel values. The optimization problem involves the maximization of the variance of the output grayscale image, the data-fitting term between the brightness of the input and output images. A regularization term is also added to make the resulting objective function to be convex and obtain a stable combination of red, green and blue pixel values. Experimental results on a set of benchmark color images are reported to demonstrate the effectiveness of the proposed method, and that its performance is better than those obtained by the other testing methods.
Original language | English |
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Pages (from-to) | 869-877 |
Number of pages | 9 |
Journal | Multidimensional Systems and Signal Processing |
Volume | 26 |
Issue number | 3 |
DOIs | |
Publication status | Published - 3 Jul 2015 |
Scopus Subject Areas
- Software
- Signal Processing
- Information Systems
- Hardware and Architecture
- Computer Science Applications
- Artificial Intelligence
- Applied Mathematics
User-Defined Keywords
- Color-to-grayscale
- Convex optimization
- Regularization