DocumentCode :
3464684
Title :
An all digital implementation of a modified Hamming net for video compression with prediction and quantization circuits
Author :
Kaul, Richard ; Adkins, Kenneth ; Bibyk, Steven
Author_Institution :
Electr. Eng., Ohio State Univ., Columbus, OH, USA
fYear :
1993
fDate :
1-3 Aug. 1993
Firstpage :
214
Lastpage :
217
Abstract :
The hardware and algorithms used to vector quantize predicted pixel intensity differences for real-time video compression are described. The hardware is designed for rapid vector quantization (VQ) performance, which entails the development of application-specific associative memory circuits. A modified DPCM algorithm is originally examined to determine how neural circuitry could enhance its operation. It was determined that quantization and encoding could be improved by consolidating these two functions into one, and by increasing the amount of information (i.e. number of pixels) quantized at a time. The result is a predictive scheme that vector quantizes differential values. Some of the disadvantages of VQ algorithms are solved using associative memories. The video compression algorithm and the associative memory design are described.<>
Keywords :
computerised picture processing; content-addressable storage; data compression; encoding; filtering and prediction theory; neural nets; pulse-code modulation; real-time systems; video signals; DPCM; associative memory circuits; computerised picture processing; encoding; modified Hamming net; neural circuitry; predicted pixel intensity; real-time; vector quantization; video compression; Associative memories; Data compression; Encoding; Filtering; Image processing; Neural networks; Pulse code modulation; Real time systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems Engineering, 1991., IEEE International Conference on
Conference_Location :
Dayton, OH, USA
Print_ISBN :
0-7803-0173-0
Type :
conf
DOI :
10.1109/ICSYSE.1991.161116
Filename :
161116
Link To Document :
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