Abstract
In this paper the problem of correlation noise modeling (CNM) for Transform Domain Wyner-Ziv (TDWZ) video coding is considered. The CNM algorithm from DISCOVER codec is analyzed. An extended set of assumptions about correlation noise in transform domain is considered and a new CNM algorithm is proposed. The proposed algorithm is a generalization of the reference one for the case of non-stationary noise. The evaluation results show that the proposed method demonstrates higher performance than the state-of-the-art approach on test video sequences with complex motion.
This work has been financially supported by the Russian Ministry of Education and Science within a framework of the basic task to the university in 2015 (project number 2452).
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Veselov, A., Filippov, B., Yastrebov, V., Gilmutdinov, M. (2015). Non-stationary Correlation Noise Modeling for Transform Domain Wyner-Ziv Video Coding. In: Damiani, E., Howlett, R., Jain, L., Gallo, L., De Pietro, G. (eds) Intelligent Interactive Multimedia Systems and Services. Smart Innovation, Systems and Technologies, vol 40. Springer, Cham. https://doi.org/10.1007/978-3-319-19830-9_17
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DOI: https://doi.org/10.1007/978-3-319-19830-9_17
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