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Performance Analysis of Multispectral Color Composite Image Enhancement Technique using Decorrelation Stretching and Histogram Equalization Methods

S. Boopathiraja1 , P. Kalavathi2 , M. Geethalakshmi3

Section:Research Paper, Product Type: Journal Paper
Volume-06 , Issue-04 , Page no. 319-323, May-2018

Online published on May 31, 2018

Copyright © S. Boopathiraja, P. Kalavathi, M. Geethalakshmi . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: S. Boopathiraja, P. Kalavathi, M. Geethalakshmi, “Performance Analysis of Multispectral Color Composite Image Enhancement Technique using Decorrelation Stretching and Histogram Equalization Methods,” International Journal of Computer Sciences and Engineering, Vol.06, Issue.04, pp.319-323, 2018.

MLA Style Citation: S. Boopathiraja, P. Kalavathi, M. Geethalakshmi "Performance Analysis of Multispectral Color Composite Image Enhancement Technique using Decorrelation Stretching and Histogram Equalization Methods." International Journal of Computer Sciences and Engineering 06.04 (2018): 319-323.

APA Style Citation: S. Boopathiraja, P. Kalavathi, M. Geethalakshmi, (2018). Performance Analysis of Multispectral Color Composite Image Enhancement Technique using Decorrelation Stretching and Histogram Equalization Methods. International Journal of Computer Sciences and Engineering, 06(04), 319-323.

BibTex Style Citation:
@article{Boopathiraja_2018,
author = {S. Boopathiraja, P. Kalavathi, M. Geethalakshmi},
title = {Performance Analysis of Multispectral Color Composite Image Enhancement Technique using Decorrelation Stretching and Histogram Equalization Methods},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2018},
volume = {06},
Issue = {04},
month = {5},
year = {2018},
issn = {2347-2693},
pages = {319-323},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=404},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=404
TI - Performance Analysis of Multispectral Color Composite Image Enhancement Technique using Decorrelation Stretching and Histogram Equalization Methods
T2 - International Journal of Computer Sciences and Engineering
AU - S. Boopathiraja, P. Kalavathi, M. Geethalakshmi
PY - 2018
DA - 2018/05/31
PB - IJCSE, Indore, INDIA
SP - 319-323
IS - 04
VL - 06
SN - 2347-2693
ER -

           

Abstract

Multispectral images are taken from remote sensing sensors which are used in wide variety of application including earth observation, distortion management and so on. An interpretation of those images for different type of applications needs to enhance for more accurate processing. In this study, we have taken the multispectral image of LANDSAT dataset which has seven bands. The color composite image is derived through combining different bands of this dataset and it is act as single color composite multispectral image. The enhancement of this multispectral color composite images is done through decorrelation stretching and the performance of this method is explained and compared with other methods such as various histogram based methods.

Key-Words / Index Term

Multispectral Image, LANDSAT, Image Enhancement, Histogram Equalization, Contrast Enhancement.

References

[1] N. Hashimoto, Y. Murakami, PA. Bautista, M. Yamaguchi, T. Obi, N. Ohyama, and Y. Kosugi, “Multispectral image enhancement for effective visualization,” Optics express, Vol.9 Issue .19, pp.9315-9329,2011.
[2] Z. Xie, and TG. Stockham, “Toward the unification of three visual laws and two visual models in brightness perception”, IEEE Transactions on Systems, Man, and Cybernetics, vol.19, issue.2, pp.379-387, 1989.
[3] A.k. Bhandari, A. Kumar, and G. K. Singh. "SVD based poor contrast improvement of blurred multispectral remote sensing satellite images.", Third International Conference Computer and Communication Technology (ICCCT), IEEE, pp.156-159. 2012.
[4] R.C. Gonzalez, and Woods,” Digital image processing” 2012.
[5] P. Kalavathi, S. Boopathiraja, and Abinaya, “Despeckling of ultrasound medical images using DW and WP transform techniques”, International Journal of Engineering and Technology (IJET), Vol. 9, issue.3, 2017.
[6] K. Somasundaram, P. Kalavathi, “Medical image contrast enhancement based on gamma correction”, Int J Knowledge Management e-learning. Vol. 3, Issue. 1, pp. 15-18, 2011.
[7] YT. Kim, “Contrast enhancement using brightness preserving bi-histogram equalization”, IEEE transactions on Consumer Electronics, vol.43, issue.1, pp.1-8. 1997.
[8] S. M. Pizer, E. P. Amburn, J. D. Austin, “Adaptive Histogram Equalization and Its Variations”, Computer Vision, Graphics, and Image Processing, vol.39, pp. 355-368, 1977.
[9] G. Adav, S. Maheshwari, and A. Agarwal,” Contrast limited adaptive histogram equalization based enhancement for real time video system”, InAdvances in Computing, Communications and Informatics (ICACCI), pp. 2392-2397, 2014.
[10] AR. Gillespie, and AB. Kahle, RE. Walker, “Color enhancement of highly correlated images. I. Decorrelation and HSI contrast stretches”, Remote Sensing of Environment, vol.20, issue.3, pp.209-35, 1986.
[11] J.M Soha, and A. Schwartz, “Multispectral histogram normalization contrast enhancement Proc”, 5th Canadian Symposium on Remote Sensing, pp. 86-93, 1978.
[12] AR. Gillespie “Enhancement of multispectral thermal infrared images: Decorrelation contrast stretching”, Remote Sensing of Environment. Vol.42, issue.2, pp.147-55, 1992.
[13] www. glovis.usgs.gov