Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/529
Title: Efficient Flexible Macroblock Ordering Technique
Authors: Psannis, Kostas E.
Ishibashi, Yutaka
Type: Article
Subjects: FRASCATI::Engineering and technology
Keywords: wireless video
error resilient algorithm
H.264/AVC
flexible macroblock ordering
Issue Date: 1-Aug-2008
Publisher: IEICE
Source: IEICE Transactions on Communications
Volume: E91-B
Issue: 8
First Page: 2692
Last Page: 2701
Abstract: The H.264/AVC standard provides several new error-resilient features to enable the reliable transmission of compressed video signals over lossy packet networks. Flexible Macroblock Ordering (FMO) is one of the most interesting resilient features within the H.264/AVC standard. Unlike former standards, in which slices were constructed out of consecutive raster scan macroblocks, FMO suggests new slices composed of spatially distributed Macroblocks (MBs), and organized in a mixed-up fashion. H.264/AVC specifies seven types of FMO. The standard defines also an explicit FMO type (Type 6), which allows explicitly assignment of each MB within the frame to any available slice groups. Therefore new FMO types can be used and integrated into H264/AVC without violating the standard. In this paper we propose a new Explicit Chessboard-Wipe (ECW) Flexible Macroblocks Ordering (FMO) technique, which outperforms all other FMO types. The new ECW ordering results in effective error scattering which maximizes the number of correctly received macroblocks located around corrupted macroblocks, leading to better error concealment. Performance evaluations demonstrate that the proposed Explicit FMO approach outperforms all the FMO types. Both subjective and objective visual quality comparative study has been also carried out in order to validate the proposed approach.
URI: https://doi.org/10.1093/ietcom/e91-b.8.2692
https://ruomo.lib.uom.gr/handle/7000/529
ISSN: 0916-8516
1745-1345
Other Identifiers: 10.1093/ietcom/e91-b.8.2692
Appears in Collections:Department of Applied Informatics

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