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Image Enhancement based on Stationary Wavelet Transform, Integer Wavelet Transform and Singular Value Decomposition

by Neena K.a, Aiswriya Raj, Rajesh Cherian Roy
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 58 - Number 11
Year of Publication: 2012
Authors: Neena K.a, Aiswriya Raj, Rajesh Cherian Roy
10.5120/9327-3632

Neena K.a, Aiswriya Raj, Rajesh Cherian Roy . Image Enhancement based on Stationary Wavelet Transform, Integer Wavelet Transform and Singular Value Decomposition. International Journal of Computer Applications. 58, 11 ( November 2012), 30-35. DOI=10.5120/9327-3632

@article{ 10.5120/9327-3632,
author = { Neena K.a, Aiswriya Raj, Rajesh Cherian Roy },
title = { Image Enhancement based on Stationary Wavelet Transform, Integer Wavelet Transform and Singular Value Decomposition },
journal = { International Journal of Computer Applications },
issue_date = { November 2012 },
volume = { 58 },
number = { 11 },
month = { November },
year = { 2012 },
issn = { 0975-8887 },
pages = { 30-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume58/number11/9327-3632/ },
doi = { 10.5120/9327-3632 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:02:12.380098+05:30
%A Neena K.a
%A Aiswriya Raj
%A Rajesh Cherian Roy
%T Image Enhancement based on Stationary Wavelet Transform, Integer Wavelet Transform and Singular Value Decomposition
%J International Journal of Computer Applications
%@ 0975-8887
%V 58
%N 11
%P 30-35
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, the image enhancement technique with respect to resolution and contrast has been proposed. The proposed method is based on bi cubic interpolation, stationary wavelet transform, discrete wavelet transform and singular value decomposition. In the proposed technique stationary wavelet transform decomposes the input image into sub bands having different frequency coefficients. The high frequency coefficients have been multiplied with the orthogonal matrix (hanger and aligner) coefficients, obtained using singular value decomposition of low resolution input image. Resulting sub bands are further added with the high frequency sub bands obtained using stationary wavelet transform. Then, the low resolution input image and high frequency sub band images are interpolated using bi cubic interpolation. Inverse integer wavelet transform has been used to combine all these sub images. Image equalization is done on this image using singular value equalization. The proposed technique is tested on different satellite images. The experimental results show the proposed method gives good results over conventional methods.

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Index Terms

Computer Science
Information Sciences

Keywords

Bi_cubic interpolation Stationary wavelet transform (SWT) Singular value decomposition (SVD) Integer wavelet transform (IWT) Inverse Integer Wavelet Transform (IIWT)

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