Data analysis for image transmitted using Discrete Wavelet Transform and Vector Quantization compression

Mustapha Khelifi, Abdelmounaim Moulay Lakhdar, Iman Elawady

Abstract


In this paper we are going to study the effect of channel noise in image compressed with vector quantization and discrete wavelet transform. The objective of this study is to analyze and understand the way that the noise attack transmitted data by doing lot of tests like dividing the indices in different levels according to discrete wavelet transform and dividing  each level in frames of bits. The collected information well helps us to propose solutions to make the received image more resistible to the channel noise also to benefit from the good representation obtained by using vector quantization and discrete wavelet transform.


Keywords


DWT; VQ; LBG; BSC channel; BER

Full Text:

PDF

References


Mohsen Nasri, Abdelhamid Helali, Halim Sghaier, Hassen Maaref. Efficient JPEG 2000 Image Compression Scheme for Multihop Wireless Networks. TELKOMNIKA.

August 2011; 9(2): 311-318.

Ali M. Fadhil, Haider M. AlSabbagh. Performance Analysis for Bit-Error-Rate of DS-CDMA Sensor Network Systems with Source Coding. TELKOMNIKA. March 2012;10(1): 165-170

Lydia Sari, Antonius Aditya. Raptor Code for Energy-Efficient Wireless Body Area Network Data Transmission. TELKOMNIKA. March 2015; 13(1) : 277-283.

Debnath, J.K , Rahim, N.M.S , Wai-Keung Fung. A modified Vector Quantization based image compression technique using wavelet transform. IEEE International Joint Conference on Neural Networks.1-8 June 2008; ISBN:978-1-4244-1821-3: 171 – 176.

Binit Amin, Patel Amrutbhai. Vector Quantization based Lossy Image Compression using Wavelets – A Review. International Journal of Innovative Research in Science, Engineering and Technology. March 2014; 3(3):10517-10523.

H Malepati ,Digital Media Processing, 1st Edition ,DSP Algorithms Using C, 20 May 2010 pp 586

Ajol Kumar Ray and Tinku Acharya, “Information Technology Principles and Applications,” Prentic Hall of India,2004.

Computer Vision and Information Technology: Advances and Applications Jan 7, 2010 by K.V. Kale and S.C. Mehrotra.pp 50

Ryszard S. Choras.Image Processing and Communications Challenges 5.Springer Science & Business Media., 19 juil. 2013 pp 236-238 un Q. Shi, Huifang Sun, “Image and Video Compression for Multimedia Engineering,” CRC Press, second edition, 2008.

Yun Q. Shi, Huifang Sun, “Image and Video Compression for Multimedia Engineering,” CRC Press, second edition, 2008.

Zhou Wang and Alan C.Bovik, “Mean squared error love it or leave it,” IEEE signal processing magazine, pp. 99-117, January. 2009.

Artificial Intelligence in Recognition and Classification of Astrophysical and Medical Images (Studies in Computational...Apr 12, 2007by Valentina Zharkova pp343

Digital Signal Processing Using MATLAB & WaveletsMar 12, 2010 by Michael Weeks pp 271

Tejas S. Patel, Ravindra Modi, Keyur J. Patel. Ima




DOI: http://dx.doi.org/10.12928/telkomnika.v14i2.2947

Article Metrics

Abstract view : 156 times
PDF - 116 times

Refbacks

  • There are currently no refbacks.


Copyright (c) 2016 Universitas Ahmad Dahlan

TELKOMNIKA Telecommunication, Computing, Electronics and Control
ISSN: 1693-6930, e-ISSN: 2302-9293
Universitas Ahmad Dahlan, 4th Campus, 9th Floor, LPPI Room
Jl. Ringroad Selatan, Kragilan, Tamanan, Banguntapan, Bantul, Yogyakarta, Indonesia 55191
Phone: +62 (274) 563515, 511830, 379418, 371120 ext. 4902, Fax: +62 274 564604

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

View TELKOMNIKA Stats