Very low bit-rate video coding using cellular neural network universal machine
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
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 language | English |
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Pages (from-to) | 153-169 |
Number of pages | 17 |
Journal | International journal of circuit theory and applications |
Volume | 27 |
Issue number | 1 |
Publication status | Published - Jan 1999 |
Peer-reviewed | Yes |
Externally published | Yes |
External IDs
ORCID | /0000-0001-7436-0103/work/142240257 |
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Keywords
ASJC Scopus subject areas
Keywords
- Cellular neural network universal machine, Very low bit-rate video coding