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Reseach Article

Lossless Grayscale Image Compression using Block-wise Entropy Shannon (LBES)

by S. Anantha Babu, P. Eswaran, C. Senthil Kumar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 146 - Number 3
Year of Publication: 2016
Authors: S. Anantha Babu, P. Eswaran, C. Senthil Kumar
10.5120/ijca2016910637

S. Anantha Babu, P. Eswaran, C. Senthil Kumar . Lossless Grayscale Image Compression using Block-wise Entropy Shannon (LBES). International Journal of Computer Applications. 146, 3 ( Jul 2016), 1-6. DOI=10.5120/ijca2016910637

@article{ 10.5120/ijca2016910637,
author = { S. Anantha Babu, P. Eswaran, C. Senthil Kumar },
title = { Lossless Grayscale Image Compression using Block-wise Entropy Shannon (LBES) },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2016 },
volume = { 146 },
number = { 3 },
month = { Jul },
year = { 2016 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume146/number3/25375-2016910637/ },
doi = { 10.5120/ijca2016910637 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:49:16.099943+05:30
%A S. Anantha Babu
%A P. Eswaran
%A C. Senthil Kumar
%T Lossless Grayscale Image Compression using Block-wise Entropy Shannon (LBES)
%J International Journal of Computer Applications
%@ 0975-8887
%V 146
%N 3
%P 1-6
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This research paper based on the probability based block wise Shanon Entropy method applied in grayscale image based on frequency occurrence of each pixel value. Then the LBES method divide the pixel with frequency of each set as assigned either 0 or 1 coding. This successful compression algorithm for utilizing optimum source coding. This theoretical idea can be proved in a range of , where H is the entropy of the source. The main Analysis of this paper is to show the better compression with other Lossless methods, with the proposed algorithm Lossless Block-wise Entropy Shannon (LBES) is suitable for produce high compression ratio 19.54 compared to other standard methods. Compression ratio is determined for all sub blocks. This process repeats for all components wise. The proposed Lossless Block-wise Entropy Shannon (LBES) is tested and implemented through quality measurement parameters such as RMSE, Entrropy, PSNR and CR by using MATLAB..

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Index Terms

Computer Science
Information Sciences

Keywords

Compression Decompression Entropy MSE and PSNR.