Multi-mode kernel-based minimum mean square error estimator for accelerated image error concealment

Koloda J, Seiler J, Peinado A, Kaup A (2016)

Publication Type: Conference contribution

Publication year: 2016

Pages Range: 612

Conference Proceedings Title: Data Compression Conference (DCC)

Event location: Snowbird, UT US

ISBN: 978-1-5090-1853-6

DOI: 10.1109/DCC.2016.55

Abstract

Summary form only given. In this paper, we propose a novel multi-mode error concealment algorithm that aims at obtaining high quality reconstructions with reduced computational burden. Block-based coding schemes in packet loss-environment are considered. The proposed technique exploits the excellent reconstructing abilities of the kernel-based minimum mean square error (K-MMSE) estimator [1]. The complexity of our technique is dynamically adapted to the visual complexity of the area being reconstructed. The technique outperforms other state of the art algorithms and produces high quality reconstructions, equivalent to K-MMSE, while requiring less than one fourth of its computational time.

Authors with CRIS profile

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

How to cite

APA:

Koloda, J., Seiler, J., Peinado, A., & Kaup, A. (2016). Multi-mode kernel-based minimum mean square error estimator for accelerated image error concealment. In Data Compression Conference (DCC) (pp. 612). Snowbird, UT, US.

MLA:

Koloda, Jan, et al. "Multi-mode kernel-based minimum mean square error estimator for accelerated image error concealment." Proceedings of the Data Compression Conference (DCC), Snowbird, UT 2016. 612.

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