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.

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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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