Low bit rate coding of image sequences using neural networks

Kalogeras, Dimitrios; Kollias, Stefanos

dc.contributor.author	Kalogeras, Dimitrios	en
dc.contributor.author	Kollias, Stefanos	en
dc.date.accessioned	2014-03-01T02:41:06Z
dc.date.available	2014-03-01T02:41:06Z
dc.date.issued	1995	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/30364
dc.subject	Communication System	en
dc.subject	Image Sequence	en
dc.subject	Neural Network	en
dc.subject	Region of Interest	en
dc.subject.other	Computer architecture	en
dc.subject.other	Computer simulation	en
dc.subject.other	Image analysis	en
dc.subject.other	Image coding	en
dc.subject.other	Image compression	en
dc.subject.other	Teleconferencing	en
dc.subject.other	Low bit rate image coding	en
dc.subject.other	Neural networks	en
dc.title	Low bit rate coding of image sequences using neural networks	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ICNN.1995.488877	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ICNN.1995.488877	en
heal.publicationDate	1995	en
heal.abstract	Neural networks are proposed in this paper as an efficient means for extending international image image sequence coding standards to achieve low bit rates for transmission in modern communication systems. In particular a structured neural network architecture is proposed for adaptively selecting regions of interest (ROI) in the images to be coded; high compression is obtained by using different quantization in each selected region region category. Simulation results illustrate the performance of the technique using videoconference sequences.	en
heal.publisher	IEEE, Piscataway, NJ, United States	en
heal.journalName	IEEE International Conference on Neural Networks - Conference Proceedings	en
dc.identifier.doi	10.1109/ICNN.1995.488877	en
dc.identifier.volume	4	en
dc.identifier.spage	1708	en
dc.identifier.epage	1712	en