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Reseach Article

Pan-sharpening based on Merged Product of Spatial Frequency Components of PAN and Intensity Images

by Megha K. Mehta, Paru Thakkar, Madhukar B. Potdar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 99 - Number 6
Year of Publication: 2014
Authors: Megha K. Mehta, Paru Thakkar, Madhukar B. Potdar
10.5120/17375-7825

Megha K. Mehta, Paru Thakkar, Madhukar B. Potdar . Pan-sharpening based on Merged Product of Spatial Frequency Components of PAN and Intensity Images. International Journal of Computer Applications. 99, 6 ( August 2014), 9-14. DOI=10.5120/17375-7825

@article{ 10.5120/17375-7825,
author = { Megha K. Mehta, Paru Thakkar, Madhukar B. Potdar },
title = { Pan-sharpening based on Merged Product of Spatial Frequency Components of PAN and Intensity Images },
journal = { International Journal of Computer Applications },
issue_date = { August 2014 },
volume = { 99 },
number = { 6 },
month = { August },
year = { 2014 },
issn = { 0975-8887 },
pages = { 9-14 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume99/number6/17375-7825/ },
doi = { 10.5120/17375-7825 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:27:28.065634+05:30
%A Megha K. Mehta
%A Paru Thakkar
%A Madhukar B. Potdar
%T Pan-sharpening based on Merged Product of Spatial Frequency Components of PAN and Intensity Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 99
%N 6
%P 9-14
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image fusion or Pan Sharpening produces high quality fused multispectral image using high spatial resolution Panchromatic (PAN) image and low spatial resolution multispectral (MS) image. The aim is to retain to a large extent both the high frequency spatial component of PAN and high spectral resolution of MS data. There are many approaches (more than 10) for image fusion based on different colour models and spatial transformations, the performances of some of which using the IKONOS-2 PAN and MS images have been evaluated earlier by the authors of this paper. In this paper, the concept of combining different spatial frequency components of the PAN and intensity images and merging with hue and saturation components is attempted on all the 10 approaches of image fusion. The technique of merging of high spatial frequency of PAN and low spatial frequency component of intensity images is described. The results of the statistical analysis show that there is marked improvement in retention of the spectral information albeit at slight loss of spatial correlation in pan-sharpening. The high level of retention of spectral information is especially significant in view of expected better classification accuracy.

References
  1. Megha K. Mehta, Nehal G. Chitaliya, Paru Thakkar and Madhukar B. Potdar, "Comparison of Performance of various Image Fusion Techniques using IKONOS-2 data", International Journal of Soft Computing and Engineering (IJSCE), vol. 3, issue 6, January-2014, pp. 232-235.
  2. Hardik Dhamecha, Tanish Zaveri and M. B. Potdar, NDVI Control based High Frequency Injection Multispectral Image Fusion Method, 2012, 978-1-4673-1159-5/12 @2012 IEEE, IGARSS-2, 2012, pp. 3513-3516.
  3. Hardik M. Dhamecha, Tanish Zaveri and Madhukar B. Potdar, A New Algorithm for Multispectral Image Fusion, IEEE-Nuicone-2011.
  4. Miloud Chikr El-Mezouar, Nasreddine Taleb, Kidiyo Kpalma and Joseph Ronsin, "An IHS-Based Fusion for Color Distortion Reduction and Vegetation Enhancement in IKONOS Imagery", IEEE Transactions On Geoscience and Remote Sensing, Vol. 49, No. 5, May 2011, pp. 1590-1602.
  5. Firouz Abdullah Al-Wassai, N. V. Kalyankar, Ali A. Al-Zuky, "The IHS Transformations Based Image Fusion", Computer Vision and Pattern Recognition (cs. CV), July 2011, pp. 1107-3348.
  6. Jaewan Choi, Kiyun Yu, and Yongil Kim, "A New Adaptive Component-Substitution-Based Satellite Image Fusion by Using Partial Replacement", IEEE Transactions On Geoscience And Remote Sensing, Vol. 49, No. 1, January 2011, pp. 295-309.
  7. Jose A. Malpica , "Hue Adjustment to IHS Pan-Sharpened IKONOS Imagery for Vegetation Enhancement", IEEE Geoscience And Remote Sensing Letters, Vol. 4, No. 1, January 2007, pp. 27-31.
  8. V. P. S. Naidu and J. R. Raol, "Pixel-level Image Fusion using Wavelets and Principal Component Analysis", Defence Science Journal, Vol. 58, No. 3, May 2008, pp. 338-352.
  9. Zhijun Wang, Djemel Ziou, Costas Armenakis, Deren Li, and Qingquan Li, "A Comparative Analysis of Image Fusion Methods", IEEE Transactions On Geoscience And Remote Sensing, Vol. 43, No. 6, June 2005, pp. 1391-1402.
  10. Myungjin Choi, "A New Intensity-Hue-Saturation Fusion Approach to Image Fusion With a Tradeoff Parameter", IEEE Transactions On Geoscience And Remote Sensing, Vol. 44, No. 6, June 2006, pp. 1672-1682.
  11. Bruno Aiazzi, Stefano Baronti, Massimo Selva, "Improving Component Substitution Pansharpening Through Multivariate Regression of MS+Pan Data", IEEE Geoscience And Remote Sensing, Vol. 45, No. 10, October 2007, pp. 3230-3239.
  12. Kazi A. Kalpoma and Jun-ichi Kudoh, "Image Fusion Processing for IKONOS 1-m Color Imagery", IEEE Geoscience And Remote Sensing, Vol. 45, No. 10, October 2007, pp. 3075-3086.
  13. T. Tu, S. Su, H. Shyu, and P. S. Huang, "A new look at his-like image fusion methods", Inf. Fusion, vol. 2, April 2001, pp. 177-186.
  14. Li S. , Kwok J. T. , Wang Y. , "Using the Discrete Wavelet Frame Transform To Merge Landsat TM And SPOT Panchromatic Images", Information Fusion 3, 2002, pp. 17–23.
  15. Hsu S. L. , Gau P. W. , Wu I L. , and Jeng J. H. , "Region-Based Image Fusion with Artificial Neural Network", World Academy of Science, Engineering and Technology, 53, 2009, pp 156 -159.
Index Terms

Computer Science
Information Sciences

Keywords

Image fusion pan sharpening spectral merging spatial merging IKONOS-2 image filtering.