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author:

Yang, Gongning (Yang, Gongning.) [1] | Wei, Xiaojie (Wei, Xiaojie.) [2] | Lin, Hongbin (Lin, Hongbin.) [3]

Indexed by:

EI

Abstract:

As video data continues to grow, the burden on network transmission increases significantly. Efficient video compression techniques are crucial to meet the rising demand for multimedia content. In this letter, we propose a Multi-scale Motion Alignment and Frame Reconstruction-based Video Codec (MFVC) for efficient video compression. MFVC focuses on optimizing the motion compensation and video reconstruction processes within a deep video compression framework. First, we design a Multi-Scale Motion Alignment Network (MSMA-Net) to achieve precise motion compensation, which extracts multi-scale features from video frames and utilizes flow information for deformable convolution. Second, we design a Frame Reconstruction Network (FR-Net) to recover high-quality video frames, which utilizes reference information for feature enhancement without additional bitrate consumption. Moreover, to achieve smooth rate adjustment, we introduce a feature scaling technique. Experimental results show that MFVC reduces bitrate by 7.86%/48.34% compared to VVC (VTM 13.2) at the same PSNR/MS-SSIM. © 1994-2012 IEEE.

Keyword:

Code division multiple access Encoding (symbols) Footage counters Forward error correction Image coding Image compression Image reconstruction Motion compensation Network coding Video recording Video signal processing

Community:

  • [ 1 ] [Yang, Gongning]Fuzhou University, Fujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information, Fuzhou; 350116, China
  • [ 2 ] [Wei, Xiaojie]Fuzhou University, Fujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information, Fuzhou; 350116, China
  • [ 3 ] [Lin, Hongbin]Fuzhou University, Fujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information, Fuzhou; 350116, China

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Source :

IEEE Signal Processing Letters

ISSN: 1070-9908

Year: 2024

Volume: 31

Page: 2125-2129

3 . 2 0 0

JCR@2023

CAS Journal Grade:3

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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