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Deep motion‐compensation enhancement in video compression.

Authors :
Prette, N.
Valsesia, D.
Bianchi, T.
Magli, E.
Naccari, M.
Fiandrotti, A.
Source :
Electronics Letters (Wiley-Blackwell); May2022, Vol. 58 Issue 11, p426-428, 3p
Publication Year :
2022

Abstract

This work introduces the multiframe motion‐compensation enhancement network (MMCE‐Net), a deep‐learning tool aimed at improving the performance of current video coding standards based on motion‐compensation, such as H.265/HEVC. The proposed method improves the inter‐prediction coding efficiency by enhancing the accuracy of the motion‐compensated frame and thereby improving the rate‐distortion performance. MMCE‐Net is a neural network that jointly exploits the predicted coding unit and two co‐located coding units from previous reference frames to improve the estimation of the temporal evolution of the scene. This letter describes the architecture of MMCE‐Net, how it is integrated into H.265/HEVC and the corresponding performance. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00135194
Volume :
58
Issue :
11
Database :
Complementary Index
Journal :
Electronics Letters (Wiley-Blackwell)
Publication Type :
Academic Journal
Accession number :
156995188
Full Text :
https://doi.org/10.1049/ell2.12475