Soft computing channel optimization for compressed and raw video data stream

Igor V. Ternovskiy; Andrew A. Kostrzewski; Aleksandr Devivye; Tomasz P. Jannson; Freddie Shing-Hong Lin

doi:10.1117/12.326711

13 October 1998 Soft computing channel optimization for compressed and raw video data stream

Igor V. Ternovskiy, Andrew A. Kostrzewski, Aleksandr Devivye, Tomasz P. Jannson, Freddie Shing-Hong Lin

Proceedings Volume 3455, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation; (1998) https://doi.org/10.1117/12.326711
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1998, San Diego, CA, United States

Abstract

Compressed and raw video data streams are discussed in the context of soft computing channel optimization, for satellite and wireless communication. Digital video data are important, since they define high-bandwidth digital data communication requirements. It would be important for channel number maximization to reduce NTSC/VGA video data throughput to audio-like channel bandwidth levels. The soft computing channel optimization combines such diversified features as: data compression, type and degree of data correlation, type of data modulation, type of error-correcting codes, and systemic/physical sources of errors.

Citation Download Citation

Igor V. Ternovskiy, Andrew A. Kostrzewski, Aleksandr Devivye, Tomasz P. Jannson, and Freddie Shing-Hong Lin "Soft computing channel optimization for compressed and raw video data stream", Proc. SPIE 3455, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation, (13 October 1998); https://doi.org/10.1117/12.326711

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KEYWORDS

Data communications

Video

Image compression

Video compression

Chromium

Platinum

Signal to noise ratio

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