P-Frame Coding with Generalized Difference: A Novel Conditional Coding Approach

Brand F, Seiler J, Kaup A (2022)

Publication Type: Conference contribution

Publication year: 2022

Publisher: IEEE

Conference Proceedings Title: 2022 IEEE International Conference on Image Processing (ICIP)

Event location: Bordeaux FR

DOI: 10.1109/ICIP46576.2022.9897294

Abstract

Motion compensated inter frame prediction is a common component of all video coders and greatly reduces temporal redundancy. With the rise of deep learning-based image and video compression, this concept has been successfully taken over from traditional coding approaches. These approaches offer a larger flexibility than traditional transform coding and therefore enable efficient conditional coding. In this work, we develop a novel conditional coding approach based on the generalized difference and generalized sum operators. This approach is a special case of a general conditional coder and has a very small complexity overhead. We also propose an extension which enables dynamic content-adaptive switching between conditional and residual coding. We show that the extended generalized difference coding outperforms both residual and conditional coding, saving 27.8% Bjøntegaard delta rate compared to the former.

Authors with CRIS profile

Fabian Brand Lehrstuhl für Multimediakommunikation und Signalverarbeitung Jürgen Seiler Lehrstuhl für Multimediakommunikation und Signalverarbeitung Andre Kaup Lehrstuhl für Multimediakommunikation und Signalverarbeitung

How to cite

APA:

Brand, F., Seiler, J., & Kaup, A. (2022). P-Frame Coding with Generalized Difference: A Novel Conditional Coding Approach. In 2022 IEEE International Conference on Image Processing (ICIP). Bordeaux, FR: IEEE.

MLA:

Brand, Fabian, Jürgen Seiler, and André Kaup. "P-Frame Coding with Generalized Difference: A Novel Conditional Coding Approach." Proceedings of the 2022 IEEE International Conference on Image Processing, Bordeaux IEEE, 2022.

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