IMPROVED IMAGE COMPRESSION BASED WAVELET TRANSFORM AND THRESHOLD ENTROPY

Article Sidebar

pdf
Published: 2011-10-01
DOI: https://doi.org/10.31026/j.eng.2011.05.09

Main Article Content

Akeel abdual aziz mohammed

Abstract

In this paper, a method is proposed to increase the compression ratio for the color images by
dividing the image into non-overlapping blocks and applying different compression ratio for these
blocks depending on the importance information of the block. In the region that contain important
information the compression ratio is reduced to prevent loss of the information, while in the
smoothness region which has not important information, high compression ratio is used .The
proposed method shows better results when compared with classical methods(wavelet and DCT).

Article Details

Issue

Vol. 17 No. 05 (2011): Journal of Engineering

Section

Articles
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

 
 

How to Cite

“IMPROVED IMAGE COMPRESSION BASED WAVELET TRANSFORM AND THRESHOLD ENTROPY” (2011) Journal of Engineering, 17(05), pp. 1152–1158. doi:10.31026/j.eng.2011.05.09.

References

Baluram Nagaria, MHD.Farukh Hashmi ,and Pradeep Dhakad, “ Comparative Analysis of Fast Wavelet Transform for Image

Compression for optimal Image Quality and Higher Compression Ratio”, International Journal of Engineering Science and

Technology (IJEST),Vol. 3 No. 5 May 2011 ,ISSN : 0975-5462.

K.Somasundaram and I.K. Raj,”Low Computational Image Compression Scheme based on Absolute Moment Block Truncation Coding “ Transactions On Engineering, Computing And Technology VO.13 MAY 2006 ISSN 1305-5313

N. D. Panagiotacopulos,K. Friesen and S. Lertsuntivit,” Lossy Image Compression Using Wavelets”, Journal of Intelligent and Robotic Systems 28: 39–59, 2000. © 2000

Kluwer Academic Publishers. Printed in the Netherlands

S.Grgic, M.Grgic., and B. Zovko-Cihlar,” Performance Analysis of Image Compression Using Wavelets” IEEE Transactions On Industrial Electronics, Vol. 48, NO. 3, JUNE 2001 pp(682-695)

Bo Li, Rui Yang, and Hongxu Jiang,” Remote-Sensing Image Compression Using Two – Dimensional Oriented Wavelet

Transform” , IEEE Transaction on Geoscience and Remote Sensing, Vol.49, NO.1, JANUARY 2011

M. K. Mandal, S. Panchanathan and T. Aboulnasr . “Choice of Wavelets for Image Compression “ , Lecture Notes in Computer Science Vol. 1133, pp. 239-249,1995

H.Gu, D. Hong, and M. Barrett ,” Wavelet Image Compressor—MinImage ”,Journal of Computational Analysis and Applications, Vol. 5, No. 1, January 2003 (# 2003)

K. R. Castleman, “Digital Image Processing”. Prentice Hall, New Jersey, 1996.

R.Steinmetz and K. Nahrstedt, “Multimedia Computing, Communications and Applications”, Prentice Hall, New Jersey,

A. Tinku,., and K.Ajoy, “ Image Processing Principles and Applications “ A John Wiley & Sons, Inc. ,Publication 2005.

C. Perrin, B. Walczak, and D. s. Massart,

“The Use of Wavelets for Signal Denoising in Capillary Electrophoresis”, Analytical Chemistry, Vol. 73, No. 20, pp.4903-4917 , October 15, 2001.

K. S. Thyagarajan,” Digital Image Processing with Application to Digital Cinema”, Focal Press 2006.