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DYNAMIC OPTIMUM DATA COMPRESSION FOR REMOTE INTERACTIVE COMMUNICATION TRANSMISSIONS

IP.com Disclosure Number: IPCOM000027077D
Original Publication Date: 1995-Feb-28
Included in the Prior Art Database: 2004-Apr-07
Document File: 2 page(s) / 116K

Publishing Venue

Xerox Disclosure Journal

Abstract

For large transmissions, information is divided along byte boundaries. The occurrence of each byte is counted and stored in a table. Usin the table, which generated. All 256 possible bytes are given a variable bit-length code which provides for maximum data compression. The large transmission contains initially the table, wherein the rest of the transmission is Huffman encoded information. The remote has software which contains the same algorithm to construct the Huffman Trees, and by doing so with the transmitted table, decodes the information into its original bytes,

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XEROX DISCLOSURE JOURNAL

DYNAMIC OPTIMUM DATA Proposed Classification COMPRESSION FOR REMOTE U.S. C1.358/260 INTERACTIVE COMMUNICATION
TRANSMISSIONS
Robert S. Hamilton

Int. C1. H04n 1/100

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Divide Data Along Byte Boundaries

on Frequency Distinct Bytes Occurrence

Compress Data Using Table to Create Huffman Encoded

Data

Transmit Table Fol lowed by

Compressed Data

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Decompress

Received Data

XEROX DISCLOSURE JOURNAL - Vol. 20, No. 1 January/February 1995 107

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DYNAMIC OPTIMUM DATA COMPRESSION FOR REMOTE INTERACTIVE COMMUNICATION TRANSMISSIONS (Cont'd)

For large transmissions, information is divided along byte boundaries. The occurrence of each byte is counted and stored in a table. Usin the table, which

generated. All 256 possible bytes are given a variable bit-length code which provides for maximum data compression. The large transmission contains initially the table, wherein the rest of the transmission is Huffman encoded information. The remote has software which contains the same algorithm to construct the Huffman Trees, and by doing so with the transmitted table, decodes the information into its original bytes,

contains each of the bytes' frequencies of occurrence, a Hu ff man Tree can be

A critical cost factor in doing large remote interactive communication transmissions is sending data via a modum. One technique for data compression is a Huffman coding algorithm. However, a statically determined Huffman Tree can actually enlarge the size of the transmission for certain sets of data which differ significantly from a most probable case. Dynamically tailoring the Huffman Tree to each set of data would be ideal. In the worse case, all bytes occurring with equal frequency, the day that ex ands by only

the data shrinks to only the size of the table. Remote interactive communication data capture contai...