CFP last date
22 April 2024
Call for Paper
May Edition
IJCA solicits high quality original research papers for the upcoming May edition of the journal. The last date of research paper submission is 22 April 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Satellite Image Compression using Kekre Wavelet Transform

Published on May 2013 by Vijaykumar P.yele, Bijith Marakarkandy
journal_cover_thumbnail

International Conference and Workshop on Emerging Trends in Technology 2014
Foundation of Computer Science USA
ICWET2014 - Number 2
May 2013
Authors: Vijaykumar P.yele, Bijith Marakarkandy
8990c37e-2e76-49fd-bf70-5d7e5d128293

Vijaykumar P.yele, Bijith Marakarkandy . Satellite Image Compression using Kekre Wavelet Transform. International Conference and Workshop on Emerging Trends in Technology 2014. ICWET2014, 2 (May 2013), 6-10.

@article{
author = { Vijaykumar P.yele, Bijith Marakarkandy },
title = { Satellite Image Compression using Kekre Wavelet Transform },
journal = { International Conference and Workshop on Emerging Trends in Technology 2014 },
issue_date = { May 2013 },
volume = { ICWET2014 },
number = { 2 },
month = { May },
year = { 2013 },
issn = 0975-8887,
pages = { 6-10 },
numpages = 5,
url = { /proceedings/icwet2014/number2/16536-1421/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference and Workshop on Emerging Trends in Technology 2014
%A Vijaykumar P.yele
%A Bijith Marakarkandy
%T Satellite Image Compression using Kekre Wavelet Transform
%J International Conference and Workshop on Emerging Trends in Technology 2014
%@ 0975-8887
%V ICWET2014
%N 2
%P 6-10
%D 2013
%I International Journal of Computer Applications
Abstract

The evolution of satellite image technology is enabling the manipulation of a greater range of data contained in increasing types of satellite images. Efficient and effective utilization of transmission bandwidth and storage capacity have been a core area of research for remote sensing images. Hence image compression is required for multi-band satellite imagery. In addition, image quality is also an important factor after compression and reconstruction. The wavelet transform is anticipated to provide economical and informative mathematical representation of many objects of interest. In the proposed system, Kekres wavelet transform is used for compression of multispectral satellite image based on compressive sampling method. The compressed image performance is analyzed using Compression Ratio (CR), Peak Signal to Noise Ratio (PSNR),Mean Square Error.

References
  1. D. Donoho, "Compressed sensing," IEEE Trans. Inform. Theory, vol. 52, no. 4, pp. 1289–1306, Apr. 2006.
  2. Emmanuel Candes` and Justin Romberg," Sparsity and incoherence in compressive sampling"Published 10 April 2007 Online atstacks. iop. org/IP/23/969
  3. Vivek K Goyal, et al"Compressive Sampling and Lossy Compression" IEEE SIGNAL PROCESSING AGAZINE,
  4. MARCH 2008
  5. Dr. H. B. Kekre et al, " Algorithm to Generate Kekre's Wavelet ransform from Kekre's Transform" International Journal of Engineering Science and Technology Vol. 2(5), 756-767, 2010
  6. Dr. H. B. Kekre, Archana Athawale & Dipali adavarti "Algorithm to Generate Wavelet Transform from an Orthogonal Transform "International Journal Of Image Processing (IJIP), Volume (4): Issue (4) 444-455 2010
  7. Multispectral Image Data Analysis System: (https://engineering. purdue. edu/~biehl/MultiSpec?)
  8. Hyper spectral image test data set: (https;//www. ehu. es/ccwintco/index. php/Hyperspecral_remote_Sensing_Scence
  9. Emmanuel J. Candès, "Compressed Sensing with Coherent and Redundant Dictionaries" Available on:http://arxiv. org/pdf/1005. 2613. pdf.
  10. Emmanuel Candes` and Justin Romberg," Sparsity and incoherence incompressive sampling"Online atstacks. iop. org/IP/23/969, 2007.
Index Terms

Computer Science
Information Sciences

Keywords

Compressive Sensing Incoherence measurement Matrix. Compression Ratio (cr) mean Square Error (mse) peak Signal To Noise Ratio (psnr)