Very low bit-rate video coding using cellular neural network universal machine

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • R. Tetzlaff - , University Hospital Frankfurt (Author)
  • R. Kunz - , University Hospital Frankfurt (Author)
  • Dietrich Wolf - , University Hospital Frankfurt (Author)

Abstract

A method of video coding for very low bit-rate channels, which is implemented using cellular neural network universal machine, is presented in the following paper. The presented method combines elements of a standard approach to video coding with elements of second-generation video-coding techniques. Inter-frame coding is performed using standard block-based motion estimation procedure, while intra-frame coding is based on vector quantization approach. To satisfy constraints imposed by very low bit-rate channel throughput, a number of bytes that were considered to be used for representing video sequence frames, was assumed to be less than 200. Simulations of the algorithm execution, based on actual CNN UM chip parameter values, show feasibility of using the proposed method for real-time implementation of very low bit-rate video coding.

Details

Original languageEnglish
Pages (from-to)153-169
Number of pages17
JournalInternational journal of circuit theory and applications
Volume27
Issue number1
Publication statusPublished - Jan 1999
Peer-reviewedYes
Externally publishedYes

External IDs

ORCID /0000-0001-7436-0103/work/142240257

Keywords

Keywords

  • Cellular neural network universal machine, Very low bit-rate video coding