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Adaptive color space model based on dominant colors for image and video compression performance improvement
S. Madenda 1, A. Darmayantie 1

1 Computer Engineering Department, Gunadarma University,
Jl. Margonda Raya. No. 100, Depok – Jawa Barat, Indonesia

 PDF, 4152 kB

DOI: 10.18287/2412-6179-CO-780

Pages: 405-417.

Full text of article: English language.

Abstract:
This paper describes the use of some color spaces in JPEG image compression algorithm and their impact in terms of image quality and compression ratio, and then proposes adaptive color space models (ACSM) to improve the performance of lossy image compression algorithm. The proposed ACSM consists of, dominant color analysis algorithm and YCoCg color space family. The YCoCg color space family is composed of three color spaces, which are YCcCr, YCpCg and YCyCb. The dominant colors analysis algorithm is developed which enables to automatically select one of the three color space models based on the suitability of the dominant colors contained in an image. The experimental results using sixty test images, which have varying colors, shapes and textures, show that the proposed adaptive color space model provides improved performance of 3 % to 10 % better than YCbCr, YDbDr, YCoCg and YCgCo-R color spaces family. In addition, the YCoCg color space family is a discrete transformation so its digital electronic implementation requires only two adders and two subtractors, both for forward and inverse conversions.

Keywords:
colors dominant analysis, adaptive color space, image compression, image quality, compression ratio.

Citation:
Madenda S, Darmayantie A. Adaptive color space model based on dominant colors for image and video compression performance improvement. Computer Optics 2021; 45(3): 405-417. DOI: 10.18287/2412-6179-CO-780.

Acknowledgements:
Thank you to Gunadarma University for providing funding support during the research and publication process.

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