DocumentCode :
1436159
Title :
True information television (TITV) breaks Shannon bandwidth barrier
Author :
Holtz, Klaus ; Holtz, Eric
Volume :
36
Issue :
2
fYear :
1990
fDate :
5/1/1990 12:00:00 AM
Firstpage :
142
Lastpage :
148
Abstract :
Concepts from artificial intelligence and learning theory are proposed for use in a knowledge-based true information TV (TITV) system. In a knowledge-based TV system a store of images is learned prior to transmission. In learn mode an image from a television camera is stored into an encoding list which is then copied to a retrieval list at the receiver. The resulting transmission bandwidth is not dependent on screen size, resolution, or scanning rate but rather only on novelty and movement. The moving portion of the input image is compared with previously learned image sections to generate superpixel codes for transmission. A superpixel may contain any size image section, from single pixel to entire images. Digital superpixel transmission promises near-perfect images for high-definition TV (HDTV) at orders of magnitude lower bandwidth and, if desired, in a virtually unbreakable encryption code
Keywords :
artificial intelligence; bandwidth compression; codes; encoding; high definition television; knowledge based systems; learning systems; television broadcasting; HDTV; Shannon bandwidth barrier; TV camera images; TV receiver; encoding list; high-definition TV; input image moving portion; knowledge-based true information TV; retrieval list; self-learning networks; superpixel transmission codes; transmitter hardware; Artificial intelligence; Bandwidth; Cameras; HDTV; Image coding; Image generation; Image retrieval; Learning; Pixel; TV receivers;
fLanguage :
English
Journal_Title :
Consumer Electronics, IEEE Transactions on
Publisher :
ieee
ISSN :
0098-3063
Type :
jour
DOI :
10.1109/30.54281
Filename :
54281
Link To Document :
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