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Contrast Enhancement of Remote Sensing Images using DWT with Kernel Filter and DTCWT

by Ruchika Mishra, Utkarsh Sharma, Manish Shrivastava
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 87 - Number 17
Year of Publication: 2014
Authors: Ruchika Mishra, Utkarsh Sharma, Manish Shrivastava
10.5120/15304-4075

Ruchika Mishra, Utkarsh Sharma, Manish Shrivastava . Contrast Enhancement of Remote Sensing Images using DWT with Kernel Filter and DTCWT. International Journal of Computer Applications. 87, 17 ( February 2014), 43-49. DOI=10.5120/15304-4075

@article{ 10.5120/15304-4075,
author = { Ruchika Mishra, Utkarsh Sharma, Manish Shrivastava },
title = { Contrast Enhancement of Remote Sensing Images using DWT with Kernel Filter and DTCWT },
journal = { International Journal of Computer Applications },
issue_date = { February 2014 },
volume = { 87 },
number = { 17 },
month = { February },
year = { 2014 },
issn = { 0975-8887 },
pages = { 43-49 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume87/number17/15304-4075/ },
doi = { 10.5120/15304-4075 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:06:12.783453+05:30
%A Ruchika Mishra
%A Utkarsh Sharma
%A Manish Shrivastava
%T Contrast Enhancement of Remote Sensing Images using DWT with Kernel Filter and DTCWT
%J International Journal of Computer Applications
%@ 0975-8887
%V 87
%N 17
%P 43-49
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image enhancement is the indispensable features in image processing to increase the contrast of the remote sensing data and to provide better transform representation of the remote image data. This paper presents a new method to improve the contrast and intensity of the image data. The method employs that the discrete wavelet transform with Kernel adaptive filtering. The performance of this algorithm is analysed and compared between EME and PSNR using simulator MATLAB 2009A.

References
  1. Sasi Gopalan, Madhu S Nair and Souriar Sebastian "Approximation Studies on Image Enhancement Using Fuzzy Technique" International Journal of Advanced Science and Technology, Vol. 10, pp. 11-26, September, 2009.
  2. S. S. Bedi, Rati Khandelwal "Various Image Enhancement Techniques- A Critical Review" International Journal of Advanced Research in Computer and Communication Engineering Vol. 2, Issue 3, March 2013
  3. Rakhi Chanana, Er. Parneet Kaur Randhawa, Er. Navneet Singh Randhawa "Spatial Domain based Image Enhancement Techniques for Scanned Electron Microscope (SEM) images" IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 4, No 2, July 2011 ISSN (Online): 1694-0814
  4. Gonzalez, Rafael C. ; Woods, Richard E. 2002. Digital Image Processing. Second Edition. Prentice Hall, New Jeresy. 2002, ISBN: 0-130-94650-8.
  5. Prof. Sumana Gupta. Digital image processing, Indian Institute of technology. [online]Published 2008. [citied1. 5. 2012].
  6. G. Veena, V. Uma, Ch. Ganapathy Reddy "Contrast Enhancement for Remote Sensing Images with Discrete Wavelet Transform", International Journal of Recent Technology and Engineering (IJRTE) ISSN: 2277-3878, Volume-2, Issue-3, July 2013
  7. Chi-Farn Chen, Hung-Yu Chang, Li-Yu Chang "A Fuzzy-Based Method For Remote Sensing Image Contrast Enhancement" The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B2. Beijing 2008
  8. Deepak Kumar Pandey, Rajesh Nema "Efficient Contrast Enhancement using Kernel Padding and DWT with Image Fusion" International Journal of Computer Applications (0975 – 8887) Volume 77– No. 15, September 2013
  9. Hasan Demirel, Cagri Ozcinar, and Gholamreza Anbarjafari," Satellite Image Contrast Enhancement Using Discrete Wavelet Transform and Singular Value Decomposition", IEEE Geoscience and Remote Sensing Letters, vol. 7, no. 2, pp. 333-337, April 2010.
  10. Eunsung Lee, S. Kim, W. Kang, D. Seo and Jooki Paik "Contrast Enhancement using Domonant Brightness Level and Adaptive Intensity Transformation for Remote Sensing Image"IEEE Geoscience and Remote sensing letters, Vol. 10, no. 1, January 2013
  11. Shujun Fu, Qiuqi Ruan, Wenqia Wang "Remote Sensing Image Data Enhancement Based on Robust Inverse Diffusion Equation for Agriculture Applications" ICSP 2008 Proceedings.
  12. Artur ?oza, David R. Bull, Paul R. Hill, Alin M . Achim "Automatic contrast enhancement of low-light images based on local statistics of wavelet coefficients", Digital Signal Processing (2013), www. elsevier. com/locate/dsp.
  13. Adin Ramirez Rivera, Byungyong Ryu, and Oksam Chae "Content Aware Dark Image Enhancement through Channel Divison"IEEE Transactions on Image Processing,volume 21,issue 9, 2012.
  14. S. E. Umbaugh, "Computer Vision & Image Processing," Prentice Hall PTR, 1998.
  15. Seyed Mohammad Entezarmahdi,and Mehran Yazdi," Stationary Image Resolution Enhancement on the Basis of Contourlet and Wavelet Transforms by means of the Artificial Neural Network", 2010 IEEE.
  16. N. G. Kingsbury, "The dual-tree complex wavelet transform with improved orthogonality and symmetry properties", IEEE international Conference on Image processing, pages 375-378, September 2000.
  17. J. Kivinen, A. Smola and R. C. Williamson. Online learning with kernels, IEEE Transactions on Signal Processing, volume 52, issue 8, pages 2165-2176, 2004.
  18. S. Mallat, "A Theory for Multiresolution Signal Decomposition: The Wavelet Representation," IEEE Pattern Analysis
Index Terms

Computer Science
Information Sciences

Keywords

Brightness Preservation Histogram Equalization Discrete Wavelet Transform Dual Tree Complex Wavelet Transform Kernel filter

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