Autosophy data/image compression and encryption

Klaus E. Holtz; Eric S. Holtz; Diana Kalienky

doi:10.1117/12.549029

18 October 2004 Autosophy data/image compression and encryption

Klaus E. Holtz, Eric S. Holtz, Diana Kalienky

Proceedings Volume 5561, Mathematics of Data/Image Coding, Compression, and Encryption VII, with Applications; (2004) https://doi.org/10.1117/12.549029
Event: Optical Science and Technology, the SPIE 49th Annual Meeting, 2004, Denver, Colorado, United States

Abstract

Multimedia data may be transmitted or stored either according to the classical Shannon information theory or according to the newer Autosophy information theory. Autosophy algorithms combine very high "lossless" data and image compression with virtually unbreakable "codebook" encryption. Shannon's theory treats all data items as "quantities", which are converted into binary digits (bit), for transmission in meaningless bit streams. Only "lossy" data compression is possible. A new "Autosophy" theory was developed by Klaus Holtz in 1974 to explain the functioning of natural self-assembling structures, such as chemical crystals or living trees. The same processes can also be used for growing self-assembling data structures, which grow like data crystals or data trees in electronic memories. This provides true mathematical learning algorithms, according to a new Autosophy information theory. Information in essence is only that which can be perceived and which is not already known by the receiver. The transmission bit rates are dependent on the data content only. Applications already include the V.42bis compression standard in modems, the gif and tif formats for lossless image compression, and Autosophy Internet television. A new 64bit data format could make all future communications compatible and solve the Internet's Quality of Service (QoS) problems.

Citation Download Citation

Klaus E. Holtz, Eric S. Holtz, and Diana Kalienky "Autosophy data/image compression and encryption", Proc. SPIE 5561, Mathematics of Data/Image Coding, Compression, and Encryption VII, with Applications, (18 October 2004); https://doi.org/10.1117/12.549029

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