Image fusion remote sensing for the extraction of urban features / Ahmad Nadzari Yahaya

Rapid advances in computer image analysis have allowed for greater flexibility and the use of techniques for combining and integrating multiresolution and multispectral data. With the multiresolution and multispectral satellites the fusion of image data has become a valuable tool in remote sensing i...

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Main Author:	Yahaya, Ahmad Nadzari
Format:	Article
Language:	English
Published:	Unit of Research, Development and Commercialization (URDC),UiTM Perlis 2004
Subjects:	Applied optics. Photonics Photoelectronic devices (General)
Online Access:	http://ir.uitm.edu.my/id/eprint/11547/ http://ir.uitm.edu.my/id/eprint/11547/1/AJ_AHMAD%20NADZARI%20SABRI%20YAHAYA%20JI%2004.pdf

id	uitm-11547
recordtype	eprints
spelling	uitm-115472016-10-10T06:25:50Z http://ir.uitm.edu.my/id/eprint/11547/ Image fusion remote sensing for the extraction of urban features / Ahmad Nadzari Yahaya Yahaya, Ahmad Nadzari Applied optics. Photonics Photoelectronic devices (General) Rapid advances in computer image analysis have allowed for greater flexibility and the use of techniques for combining and integrating multiresolution and multispectral data. With the multiresolution and multispectral satellites the fusion of image data has become a valuable tool in remote sensing image evaluation. This study evaluated several methods to enhance the spatial resolution of multispectral images using a higher resolution panchromatic image. This was performed using Landsat7 ETM+Multispectral bands and Pancromatic band imagery satellite. The Landsat7 ETM+ panchromatic band is taken simultaneously with multispectral bands using the same system, therefore, are co-registered accurately. The study involved image and theme enhancement by applying Optimum Index Factor(OIF) using three techniques of image fusion : Intensity-Hue-Saturation(IHS), Brovey and Principal Component Analysis(PCA). Brovey was observed to be the best fusion technique for extraction urban features with respect to less spatial and spectral distortion as well as visualization. OIF is a powerful technique for the analysis and visualization of urban features. Based on training samples, ETM+ multispectral and fused images were subjected to the process of Iterative Self-Organizing Data Analysis (ISODATA) techniques using maximum likelihood decision rule to derive the classification of urban features classes. Signature separability using transformed divergence was used to evaluate between signature classes for classification. Ground truth for classification accuracy assessment were evaluated using error matrix and overall classification techniques. This would display the advantages and results of fused images classification. Unit of Research, Development and Commercialization (URDC),UiTM Perlis 2004 Article PeerReviewed text en http://ir.uitm.edu.my/id/eprint/11547/1/AJ_AHMAD%20NADZARI%20SABRI%20YAHAYA%20JI%2004.pdf Yahaya, Ahmad Nadzari (2004) Image fusion remote sensing for the extraction of urban features / Ahmad Nadzari Yahaya. Jurnal Intelek, 2 (1). pp. 31-38. ISSN 2231-7716
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
language	English
topic	Applied optics. Photonics Photoelectronic devices (General)
spellingShingle	Applied optics. Photonics Photoelectronic devices (General) Yahaya, Ahmad Nadzari Image fusion remote sensing for the extraction of urban features / Ahmad Nadzari Yahaya
description	Rapid advances in computer image analysis have allowed for greater flexibility and the use of techniques for combining and integrating multiresolution and multispectral data. With the multiresolution and multispectral satellites the fusion of image data has become a valuable tool in remote sensing image evaluation. This study evaluated several methods to enhance the spatial resolution of multispectral images using a higher resolution panchromatic image. This was performed using Landsat7 ETM+Multispectral bands and Pancromatic band imagery satellite. The Landsat7 ETM+ panchromatic band is taken simultaneously with multispectral bands using the same system, therefore, are co-registered accurately. The study involved image and theme enhancement by applying Optimum Index Factor(OIF) using three techniques of image fusion : Intensity-Hue-Saturation(IHS), Brovey and Principal Component Analysis(PCA). Brovey was observed to be the best fusion technique for extraction urban features with respect to less spatial and spectral distortion as well as visualization. OIF is a powerful technique for the analysis and visualization of urban features. Based on training samples, ETM+ multispectral and fused images were subjected to the process of Iterative Self-Organizing Data Analysis (ISODATA) techniques using maximum likelihood decision rule to derive the classification of urban features classes. Signature separability using transformed divergence was used to evaluate between signature classes for classification. Ground truth for classification accuracy assessment were evaluated using error matrix and overall classification techniques. This would display the advantages and results of fused images classification.
format	Article
author	Yahaya, Ahmad Nadzari
author_facet	Yahaya, Ahmad Nadzari
author_sort	Yahaya, Ahmad Nadzari
title	Image fusion remote sensing for the extraction of urban features / Ahmad Nadzari Yahaya
title_short	Image fusion remote sensing for the extraction of urban features / Ahmad Nadzari Yahaya
title_full	Image fusion remote sensing for the extraction of urban features / Ahmad Nadzari Yahaya
title_fullStr	Image fusion remote sensing for the extraction of urban features / Ahmad Nadzari Yahaya
title_full_unstemmed	Image fusion remote sensing for the extraction of urban features / Ahmad Nadzari Yahaya
title_sort	image fusion remote sensing for the extraction of urban features / ahmad nadzari yahaya
publisher	Unit of Research, Development and Commercialization (URDC),UiTM Perlis
publishDate	2004
url	http://ir.uitm.edu.my/id/eprint/11547/ http://ir.uitm.edu.my/id/eprint/11547/1/AJ_AHMAD%20NADZARI%20SABRI%20YAHAYA%20JI%2004.pdf
first_indexed	2023-09-18T22:48:09Z
last_indexed	2023-09-18T22:48:09Z
_version_	1777417363748028416

Image fusion remote sensing for the extraction of urban features / Ahmad Nadzari Yahaya

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