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Satellite Image Compression using Fractional Fourier Transform

by Rajinder Kumar, Kulbir Singh, Rajesh Khanna
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 50 - Number 3
Year of Publication: 2012
Authors: Rajinder Kumar, Kulbir Singh, Rajesh Khanna
10.5120/7752-0810

Rajinder Kumar, Kulbir Singh, Rajesh Khanna . Satellite Image Compression using Fractional Fourier Transform. International Journal of Computer Applications. 50, 3 ( July 2012), 20-25. DOI=10.5120/7752-0810

@article{ 10.5120/7752-0810,
author = { Rajinder Kumar, Kulbir Singh, Rajesh Khanna },
title = { Satellite Image Compression using Fractional Fourier Transform },
journal = { International Journal of Computer Applications },
issue_date = { July 2012 },
volume = { 50 },
number = { 3 },
month = { July },
year = { 2012 },
issn = { 0975-8887 },
pages = { 20-25 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume50/number3/7752-0810/ },
doi = { 10.5120/7752-0810 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:47:22.635462+05:30
%A Rajinder Kumar
%A Kulbir Singh
%A Rajesh Khanna
%T Satellite Image Compression using Fractional Fourier Transform
%J International Journal of Computer Applications
%@ 0975-8887
%V 50
%N 3
%P 20-25
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The Fourier transform can be successfully used in the field of signal processing, image processing, communications and data compression applications. The discrete fractional Fourier transform, generalization of the discrete Fourier transform, is used for compression of high resolution satellite images. With the extra degree of freedom provided by the DFrFT, its fractional order 'a', high visual quality decompressed image can be achieved. Different satellite images of size 512×512 and 256×256 are studied and performance parameters such as peak signal-to-noise ratio (PSNR), mean square error (MSE) and compression ratio (CR) are determined. After subdivide the images, DFrFt is applied to obtain the transformed coefficients for calculating PSNR and IDFrFt is applied for reconstruction of satellite images. It is analyzed that by changing the value of fractional order 'a' to different value, the DFrFT can achieved minimum MSE and corresponding maximum PSNR between 0. 8 to 1 fractional order for same amount of CR. It is observed that discrete fractional Fourier transform is very efficient for obtaining better PSNR around 41 dB at 50% CR while maintaining the higher visual quality of decompressed satellite images. The significant improvement is observed using DFrFT as compare to existing classical lifting scheme for satellite image compression based on discrete wavelet transform (DWT).

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Index Terms

Computer Science
Information Sciences

Keywords

Satellite Image Compression DFrFT PSNR MSE

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