A STUDY ON THE EFFECT OF COLOR SPACES IN LEARNED IMAGE COMPRESSION

Prativadibhayankaram S, Panda MP, Seiler J, Richter T, Sparenberg H, Foessel S, Kaup A (2024)

Publication Type: Conference contribution

Publication year: 2024

Journal

Proceedings - International Conference on Image Processing, ICIP

Publisher: IEEE Computer Society

Pages Range: 3744-3750

Conference Proceedings Title: Proceedings - International Conference on Image Processing, ICIP

Event location: Abu Dhabi, ARE

ISBN: 9798350349399

DOI: 10.1109/ICIP51287.2024.10648167

Abstract

In this work, we present a comparison between color spaces namely YUV, LAB, RGB and their effect on learned image compression. For this we use the structure and color based learned image codec (SLIC) from our prior work, which consists of two branches-one for the luminance component (Y or L) and another for chrominance components (UV or AB). However, for the RGB variant we input all 3 channels in a single branch, similar to most learned image codecs operating in RGB. The models are trained for multiple bitrate configurations in each color space. We report the findings from our experiments by evaluating them on various datasets and compare the results to state-of-the-art image codecs. The YUV model performs better than the LAB variant in terms of MS-SSIM with a Bjøntegaard delta bitrate (BD-BR) gain of 7.5% using VTM intra-coding mode as the baseline. Whereas the LAB variant has a better performance than YUV model in terms of CIEDE2000 having a BD-BR gain of 8%. Overall, the RGB variant of SLIC achieves the best performance with a BD-BR gain of 13.14% in terms of MS-SSIM and a gain of 17.96% in CIEDE2000 at the cost of a higher model complexity.

Authors with CRIS profile

Jürgen Seiler Lehrstuhl für Multimediakommunikation und Signalverarbeitung (LMS) Andre Kaup Lehrstuhl für Multimediakommunikation und Signalverarbeitung (LMS)

Involved external institutions

Fraunhofer-Institut für Integrierte Schaltungen (IIS) DE Germany (DE)

How to cite

APA:

Prativadibhayankaram, S., Panda, M.P., Seiler, J., Richter, T., Sparenberg, H., Foessel, S., & Kaup, A. (2024). A STUDY ON THE EFFECT OF COLOR SPACES IN LEARNED IMAGE COMPRESSION. In Proceedings - International Conference on Image Processing, ICIP (pp. 3744-3750). Abu Dhabi, ARE: IEEE Computer Society.

MLA:

Prativadibhayankaram, Srivatsa, et al. "A STUDY ON THE EFFECT OF COLOR SPACES IN LEARNED IMAGE COMPRESSION." Proceedings of the 31st IEEE International Conference on Image Processing, ICIP 2024, Abu Dhabi, ARE IEEE Computer Society, 2024. 3744-3750.

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