Dynamic model selection during data compression

A computerized method of dynamically selecting the best of a plurality of data compression models for use in arithmetic coding and decoding wherein each model generates a string of data in response to a stream of input symbols, comprising the steps of:

• beginning with the same symbol in said input symbol stream, using each of said models to produce respective strings of data from said input symbols including a model selection decision for the respective model;
• coding the model selection decision and the string of data for each model with an adaptive arithmetic coder to generate respective blocks of compressed data for each model, with each of said blocks being of at least a given size and starting the coding of each model for a given block with the same code stream and probability interval;
• and
• selecting the model with the best coding performance from among the blocks of compressed data generated during the arithmetic coding on the basis of the amount of input symbol data compressed.

A computerized system for maximizing the compression of a stream of input symbols by dynamically selecting the best of a plurality of data compression models for respectively encoding each of successive portions of said stream, wherein each model, in response to input symbols, generates encoded data, based on model characteristics, in the form of respective strings of data, comprising:

• means, beginning with the same input symbol in said stream, for generating respective strings of data from the stream of input symbols using each of said data compression models;
• means for compression coding said strings of data to produce respective blocks of compressed data, each of said blocks being at least equal to a given size;
• means for selecting the respective block of compressed data for which the most input symbols have been compressed;
• means for adding the selected block of compressed data to an output data stream;
• and
• means for actuating said foregoing means to act on the next succeeding portion of said input symbol stream, beginning with the input symbol following the last symbol input to said selected model, until all of the portions of said input stream have been compressed and added to said output data stream.

A computerized system for dynamically selecting one of a plurality of data compression models for use in arithmetic coding and decoding wherein each model generates a string of data in response to a stream of input symbols, comprising the steps of:

• means, beginning with the same symbol in said input symbol stream, for producing respective strings of data from said input symbols using each of said models and including a model selection decision for the respective model;
• adaptive arithmetic coder means for coding the model selection decision and the string of data for each model to generate respective blocks of compressed data for each model, with each of said blocks being of at least a given size and starting the coding of each model for a given block with the same code stream and probability interval;
• and
• means for selecting the model with the optimum coding performance from among the blocks of compressed data generated during the arithmetic coding on the basis of the amount of input symbol data compressed.