Khudhair, Zaid Nidhal and Khdiar, Ahmed Nidhal and El Abbadi, Nidhal K. and Mohamed, Farhan and Saba, Tanzila and Alamri, Faten S. and Rehman, Amjad (2023) Color to grayscale image conversion based on singular value decomposition. IEEE Access, 11 . pp. 54629-54638. ISSN 2169-3536
PDF
1MB |
Official URL: http://dx.doi.org/10.1109/ACCESS.2023.3279734
Abstract
Color information is useless for distinguishing significant edges and features in numerous applications. In image processing, a gray image discards much-unrequired data in a color image. The primary drawback of colour-to-grey conversion is eliminating the visually significant image pixels. A current proposal is a novel approach for transforming an RGB image into a grayscale image based on singular value decomposition (SVD). A specific factor magnifies one of the color channels (Red, Green, and Blue). A vector of three values (Red, Green, Blue) of each pixel in an image is decomposed using SVD into three matrices. The norm of the diagonal matrix was determined and then divided by a specific factor to obtain the grey value of the corresponding pixel. The contribution of the proposed method gives the user high flexibility to produce many versions of gray images with varying contrasts, which is very helpful in many applications. Furthermore, SVD allows for image reconstruction by combining the weighting of each channel with the singular value matrix. This results in a grayscale image that more accurately captures the actual intensity values of the image and preserves more color information than traditional grayscale conversion methods, resulting in loss of color information. The proposed method was compared with a similar method (converting the color image into grayscale) and was found to be the most efficient.
Item Type: | Article |
---|---|
Uncontrolled Keywords: | Decolorization; grey image; image conversion; SVD; technological development |
Subjects: | T Technology > T Technology (General) > T58.6-58.62 Management information systems |
Divisions: | Computer Science and Information System |
ID Code: | 104890 |
Deposited By: | Muhamad Idham Sulong |
Deposited On: | 25 Mar 2024 09:23 |
Last Modified: | 25 Mar 2024 09:23 |
Repository Staff Only: item control page