BAND REDUCTION FOR TARGET DETECTION IN HYPERSPECTRAL IMAGES

Murat Şimşek; Hakki Alparslan Ilgın

doi:10.33769/aupse.676083

Araştırma Makalesi

BAND REDUCTION FOR TARGET DETECTION IN HYPERSPECTRAL IMAGES

Yıl 2020, Cilt: 62 Sayı: 1, 53 - 62, 30.06.2020

Murat Şimşek Hakki Alparslan Ilgın

https://doi.org/10.33769/aupse.676083

Öz

Due to the high spectral resolution, hyperspectral images need large data storage and processing time. Indeed, its high dimensional structure requires high computational complexity, especially for target detection. In order to overcome these problems, band reduction methods have been proposed. In this paper, we compare PCA and SNR-based band reduction methods to improve target detection performance in hyperspectral images. Experimental results show that band reduction methods not only reduce processing time, but also increase accuracy rate.

Anahtar Kelimeler

Hyperspectral image, band reduction, target detection

Kaynakça

Marwaha, R. and Kumar, A., Target Detection Algorithm for Airborne Thermal Hyperspectral Data, ISPRS Technical Commission VIII Symposium, Volume XL-8, 2014.
RIT (Rochester Institute of Technology) 2006, Chooke City Hyperspectral Data Set http://dirsapps.cis.rit.edu/blindtest/download. Last access date: 24.07.2019.
Rodarmel, C. and Shan, J., Principal Component Analysis for Hyperspectral Image Classification, Surveying and Land Information Science, 62(2), (2002), 115-122.
Gonzalez, R. and Woods, R., Digital Image Processing, Reading, Massachusetts, Addison-Wesley Publishing Company. pp.148-56, 1993.
Mallapragada, S., Wong, M. and Hung, C., Dimensionality Reduction of Hyperspectral Images for Classification, Ninth International Conference on Information, Tokyo, Japan, 2018.
Vaiphasa, C., Consideration of Smoothing Techniques for Hyperspectral Remote Sensing, ISPRS Journal of Photogrammetry and Remote Sensing, 60, Elsevier, New York, (2006), 91-99.
ITT Visual Information Solutions, (ENVI User’s Guide), 2009.
Jin, X., Paswaters, S. and Cline, H., A Comparative Study of Target Detection Algorithms for Hyperspectral Imagery, Proc. SPIE 7334, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV, 73341W , 2009.
Gordon, C., A Generalization of the Maximum Noise Fraction Transform, IEEE Trans. Geosci. Remote Sens., 38, (2000), 608–610.
Manolakis, D. and Shaw, G., Detection Algorithms for Hyperspectral İmaging Applications, Signal Processing, 2002.

Yıl 2020, Cilt: 62 Sayı: 1, 53 - 62, 30.06.2020

Murat Şimşek Hakki Alparslan Ilgın

https://doi.org/10.33769/aupse.676083

Öz

Kaynakça

Marwaha, R. and Kumar, A., Target Detection Algorithm for Airborne Thermal Hyperspectral Data, ISPRS Technical Commission VIII Symposium, Volume XL-8, 2014.
RIT (Rochester Institute of Technology) 2006, Chooke City Hyperspectral Data Set http://dirsapps.cis.rit.edu/blindtest/download. Last access date: 24.07.2019.
Rodarmel, C. and Shan, J., Principal Component Analysis for Hyperspectral Image Classification, Surveying and Land Information Science, 62(2), (2002), 115-122.
Gonzalez, R. and Woods, R., Digital Image Processing, Reading, Massachusetts, Addison-Wesley Publishing Company. pp.148-56, 1993.
Mallapragada, S., Wong, M. and Hung, C., Dimensionality Reduction of Hyperspectral Images for Classification, Ninth International Conference on Information, Tokyo, Japan, 2018.
Vaiphasa, C., Consideration of Smoothing Techniques for Hyperspectral Remote Sensing, ISPRS Journal of Photogrammetry and Remote Sensing, 60, Elsevier, New York, (2006), 91-99.
ITT Visual Information Solutions, (ENVI User’s Guide), 2009.
Jin, X., Paswaters, S. and Cline, H., A Comparative Study of Target Detection Algorithms for Hyperspectral Imagery, Proc. SPIE 7334, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV, 73341W , 2009.
Gordon, C., A Generalization of the Maximum Noise Fraction Transform, IEEE Trans. Geosci. Remote Sens., 38, (2000), 608–610.
Manolakis, D. and Shaw, G., Detection Algorithms for Hyperspectral İmaging Applications, Signal Processing, 2002.

Toplam 10 adet kaynakça vardır.

Ayrıntılar

Birincil Dil	İngilizce
Konular	Mühendislik
Bölüm	Research Article
Yazarlar	Murat Şimşek 0000-0002-8648-3693 Hakki Alparslan Ilgın 0000-0003-0112-4833
Yayımlanma Tarihi	30 Haziran 2020
Gönderilme Tarihi	16 Ocak 2020
Kabul Tarihi	10 Şubat 2020
Yayımlandığı Sayı	Yıl 2020 Cilt: 62 Sayı: 1

Kaynak Göster

APA	Şimşek, M., & Ilgın, H. A. (2020). BAND REDUCTION FOR TARGET DETECTION IN HYPERSPECTRAL IMAGES. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering, 62(1), 53-62. https://doi.org/10.33769/aupse.676083
AMA	Şimşek M, Ilgın HA. BAND REDUCTION FOR TARGET DETECTION IN HYPERSPECTRAL IMAGES. Commun.Fac.Sci.Univ.Ank.Series A2-A3: Phys.Sci. and Eng. Haziran 2020;62(1):53-62. doi:10.33769/aupse.676083
Chicago	Şimşek, Murat, ve Hakki Alparslan Ilgın. “BAND REDUCTION FOR TARGET DETECTION IN HYPERSPECTRAL IMAGES”. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering 62, sy. 1 (Haziran 2020): 53-62. https://doi.org/10.33769/aupse.676083.
EndNote	Şimşek M, Ilgın HA (01 Haziran 2020) BAND REDUCTION FOR TARGET DETECTION IN HYPERSPECTRAL IMAGES. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering 62 1 53–62.
IEEE	M. Şimşek ve H. A. Ilgın, “BAND REDUCTION FOR TARGET DETECTION IN HYPERSPECTRAL IMAGES”, Commun.Fac.Sci.Univ.Ank.Series A2-A3: Phys.Sci. and Eng., c. 62, sy. 1, ss. 53–62, 2020, doi: 10.33769/aupse.676083.
ISNAD	Şimşek, Murat - Ilgın, Hakki Alparslan. “BAND REDUCTION FOR TARGET DETECTION IN HYPERSPECTRAL IMAGES”. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering 62/1 (Haziran 2020), 53-62. https://doi.org/10.33769/aupse.676083.
JAMA	Şimşek M, Ilgın HA. BAND REDUCTION FOR TARGET DETECTION IN HYPERSPECTRAL IMAGES. Commun.Fac.Sci.Univ.Ank.Series A2-A3: Phys.Sci. and Eng. 2020;62:53–62.
MLA	Şimşek, Murat ve Hakki Alparslan Ilgın. “BAND REDUCTION FOR TARGET DETECTION IN HYPERSPECTRAL IMAGES”. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering, c. 62, sy. 1, 2020, ss. 53-62, doi:10.33769/aupse.676083.
Vancouver	Şimşek M, Ilgın HA. BAND REDUCTION FOR TARGET DETECTION IN HYPERSPECTRAL IMAGES. Commun.Fac.Sci.Univ.Ank.Series A2-A3: Phys.Sci. and Eng. 2020;62(1):53-62.