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A Compression Algorithm Using Variable-to-Fixed Block Arithmetic Codes


Affiliations
1 Department of Computer Science, R.I.T., Goa, India
 

In this paper a method for lossless image compression which will produce a better results in terms of overall compression ratio for bi-level images is introduced. This algorithm uses the Block Arithmetic Coding for Image Compression (BACIC) algorithm. For the purpose of compression it uses variable-to-fixed arithmetic coder called Block Arithmetic Coder (BAC)which is a a technique for entropy coding that combines many of the advantages of ordinary stream arithmetic coding with the simplicity of block codes. The code is variable length in to fixed out (V to F), in which the source sequence of bits is partitioned into variable length that are encoded by a fixed length sequences of bits.

 Arithmetic coding assumes an explicit probabilistic model of the source. So, this models uses the estimation of probability that serves as an index into a probability table and used to compute p1 (the probability of a bit equaling one), the probability measure BAC needs to compute a codeword.


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  • A Compression Algorithm Using Variable-to-Fixed Block Arithmetic Codes

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Authors

Anurag Jain
Department of Computer Science, R.I.T., Goa, India

Abstract


In this paper a method for lossless image compression which will produce a better results in terms of overall compression ratio for bi-level images is introduced. This algorithm uses the Block Arithmetic Coding for Image Compression (BACIC) algorithm. For the purpose of compression it uses variable-to-fixed arithmetic coder called Block Arithmetic Coder (BAC)which is a a technique for entropy coding that combines many of the advantages of ordinary stream arithmetic coding with the simplicity of block codes. The code is variable length in to fixed out (V to F), in which the source sequence of bits is partitioned into variable length that are encoded by a fixed length sequences of bits.

 Arithmetic coding assumes an explicit probabilistic model of the source. So, this models uses the estimation of probability that serves as an index into a probability table and used to compute p1 (the probability of a bit equaling one), the probability measure BAC needs to compute a codeword.