Implementation of Huffman algorithm and study for optimization

Popular lossless data compression algorithms like DEFLATE and GZIP use Huffman encoding method as the primary tool for compression. Data compression or signal compression plays a vital role in signal processing. This paper aims to explain Huffman encoding method for lossless data compression, its functionality is demonstrated using MATLAB tool and simulation is done over simulation software with the program written in VHDL. The need of optimization has given wide variations in Huffman encoding and decoding process. The vital factors that have to be focused on for achieving optimization in the codes generated by traditional Huffman encoders are also evaluated and discussed in this paper.

[1]  Chin-Chen Chang,et al.  An efficient Huffman decoding method based on pattern partition and look-up table , 1999, Fifth Asia-Pacific Conference on ... and Fourth Optoelectronics and Communications Conference on Communications,.

[2]  W. Bishop,et al.  FPGA-Based Lossless Data Compression using Huffman and LZ77 Algorithms , 2007, 2007 Canadian Conference on Electrical and Computer Engineering.

[3]  Mahmoud Reza Hashemi,et al.  A simple lossless preprocessing algorithm for hardware implementation of Deflate data compression , 2011, 2011 19th Iranian Conference on Electrical Engineering.

[4]  Glen G. Langdon,et al.  An Introduction to Arithmetic Coding , 1984, IBM J. Res. Dev..

[5]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[6]  Taeyeon Lee,et al.  Design and implementation of static Huffman encoding hardware using a parallel shifting algorithm , 2004 .

[7]  Jhing-Fa Wang,et al.  Design and hardware architectures for dynamic Huffman coding , 1995 .

[8]  D. Huffman A Method for the Construction of Minimum-Redundancy Codes , 1952 .

[9]  Thomas M. Cover,et al.  On the competitive optimality of Huffman codes , 1991, IEEE Trans. Inf. Theory.

[10]  Hatsukazu Tanaka,et al.  Data structure of Huffman codes and its application to efficient encoding and decoding , 1987, IEEE Trans. Inf. Theory.

[11]  Julia Abrahams,et al.  Code and parse tree for lossless source encoding , 2001, Commun. Inf. Syst..

[12]  Weijia Jia,et al.  Optimal maximal and maximal prefix codes equivalent to Huffman codes , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[13]  Ian H. Witten,et al.  Text Compression , 1990, 125 Problems in Text Algorithms.