Open AccessImage compression using singular value decomposition by extracting red, green, and blue channel colors
Author(s) -
Shamsul Fakhar Abd Gani,
Rostam Affendi Hamzah,
Ramlan Latip,
Sazilah Salam,
Fatin Noraqillah,
Adi Irwan Herman
Publication year - 2022
Publication title -
bulletin of electrical engineering and informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.251
H-Index - 12
ISSN - 2302-9285
DOI - 10.11591/eei.v11i1.2602
Subject(s) - computer science , rgb color model , image compression , artificial intelligence , singular value decomposition , computer vision , codec , data compression , image quality , color image , channel (broadcasting) , lossless compression , image (mathematics) , image processing , computer hardware , telecommunications
This paper presents an image compression using singular value decomposition (SVD) by extracting the red, green, and blue (RGB) channel colors. Image compression is needed in the development of various multimedia computer services and applications for example in the telecommunications and storage technologies. Now a days, video technology, digital broadcast codec and teleconferencing become popular and always requires high image compression process for display. Hence, efficient image compression is compulsory to reduce the number of storage sizes and maintain the image quality. Therefore, this article proposes image compression using SVD, which this method is efficiently reducing the image storage size and at the same time maintaining the image quality. The SVD removes redundant pixel values based on RGB colors to make the storage image size decreased. Based on the experimental analysis on two different type of image extensions (i.e., jpg and png), the SVD is capable to reduce the image size and at the same time preserving the image quality.