In-loop noise-filtered prediction for high efficiency video coding

Wige E, Yammine G, Amon P, Hutter A, Kaup A (2014)


Publication Status: Published

Publication Type: Journal article, Original article

Publication year: 2014

Journal

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Book Volume: 24

Pages Range: 1142-1155

Article Number: 6727435

Journal Issue: 7

DOI: 10.1109/TCSVT.2014.2302377

Abstract

In this paper, we focus on optimization and enhancement of High Efficiency Video Coding (HEVC) with respect to professional applications. In most of the professional video applications, noise dominates the compression performance. We therefore theoretically and practically analyze the denoising performance of an HEVC codec and show that, especially for low to medium quantization parameters (QPs), the source noise is still present in the reconstructed frame. This motivates us to use an explicit in-loop reference frame denoising filter for this quality range. We show how the noise, which badly influences the prediction, can be modeled and estimated. Two approaches are introduced, in which either the noise is calculated from prior knowledge or estimated automatically without prior knowledge. A denoising filter that exploits the HEVC core transform is introduced. Finally, a coding mode adaptive scheme for motion compensation using the noise-filtered reference frame is described. The compression results show that especially for low to medium QP settings as well as lossless compression considerable bitrate savings can be achieved using the proposed schemes. © 1991-2012 IEEE.

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How to cite

APA:

Wige, E., Yammine, G., Amon, P., Hutter, A., & Kaup, A. (2014). In-loop noise-filtered prediction for high efficiency video coding. IEEE Transactions on Circuits and Systems For Video Technology, 24(7), 1142-1155. https://dx.doi.org/10.1109/TCSVT.2014.2302377

MLA:

Wige, Eugen, et al. "In-loop noise-filtered prediction for high efficiency video coding." IEEE Transactions on Circuits and Systems For Video Technology 24.7 (2014): 1142-1155.

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