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Reseach Article

Image Compression Based on Wavelet and Quantization with Optimal Huffman Code

by Munesh Chandra Adhikary, Ashanta Ranjan Routray
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 5 - Number 2
Year of Publication: 2010
Authors: Munesh Chandra Adhikary, Ashanta Ranjan Routray
10.5120/893-1267

Munesh Chandra Adhikary, Ashanta Ranjan Routray . Image Compression Based on Wavelet and Quantization with Optimal Huffman Code. International Journal of Computer Applications. 5, 2 ( August 2010), 6-9. DOI=10.5120/893-1267

@article{ 10.5120/893-1267,
author = { Munesh Chandra Adhikary, Ashanta Ranjan Routray },
title = { Image Compression Based on Wavelet and Quantization with Optimal Huffman Code },
journal = { International Journal of Computer Applications },
issue_date = { August 2010 },
volume = { 5 },
number = { 2 },
month = { August },
year = { 2010 },
issn = { 0975-8887 },
pages = { 6-9 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume5/number2/893-1267/ },
doi = { 10.5120/893-1267 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:53:10.412700+05:30
%A Munesh Chandra Adhikary
%A Ashanta Ranjan Routray
%T Image Compression Based on Wavelet and Quantization with Optimal Huffman Code
%J International Journal of Computer Applications
%@ 0975-8887
%V 5
%N 2
%P 6-9
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper proposes a method for the compression of color images by Haar transform, quantization and construction of minimum redundancy code using conventional Huffman coding. Wavelet compression is accomplished by decomposing the row and column of the image matrix using the Harr transform. And the reconstruction of the image is feasible just from 1/4th of the decomposed image and even 1/16th of the decomposed image is enough for re-construction and the quality relies on the nature the image. A fast and effective histogram-based quantization is applied to the decomposed image. The weighted minmax quantization incorporates activity weighting, whereby obtaining high quality quantized image with significantly less visual distortion. Partition based Huffman coding divides symbols based on sorted probabilities of symbols into two equal halves and generates codes for each portioned symbols. Analytical and experimental results suggest that the optimum code can be generated for images with balanced binary partition Huffman coding, which is not only decodable but also offers the possibility of realizing an average code-word length that can be made arbitrarily close to the source entropy.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Entropy Haar Transform Quantization Huffman code