Image quality assessment for fused remote sensing imageries
Image fusion provides precise information in both spatial and spectral resolutions that benefit significantly in high accuracy mapping. Yet, there is less intention withdrawn in justifying the performance of the fused image. In this study, qualitative and quantitative assessments were carried out to...
Saved in:
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
Penerbit UTM
2014
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/53072/1/MohdNadzriMd2014_Imagequalityassessmentforfused.pdf http://eprints.utm.my/id/eprint/53072/ http://dx.doi.org/10.11113/jt.v71.3839 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Universiti Teknologi Malaysia |
Language: | English |
id |
my.utm.53072 |
---|---|
record_format |
eprints |
spelling |
my.utm.530722018-07-19T07:23:50Z http://eprints.utm.my/id/eprint/53072/ Image quality assessment for fused remote sensing imageries Md. Reba, Mohd. Nadzri C’uang, Ong Juey HD Industries. Land use. Labor Image fusion provides precise information in both spatial and spectral resolutions that benefit significantly in high accuracy mapping. Yet, there is less intention withdrawn in justifying the performance of the fused image. In this study, qualitative and quantitative assessments were carried out to test the quality of fusion image. Principal Component Analysis (PCA), Gram-Schmidt and Ehlers were applied to fuse the hyperspectral and Lidar image. Ehlers fusion showed good in preserving the color of image and contained the most information. Besides, the classification of Ehlers fused image showed the highest accuracy. Penerbit UTM 2014 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/53072/1/MohdNadzriMd2014_Imagequalityassessmentforfused.pdf Md. Reba, Mohd. Nadzri and C’uang, Ong Juey (2014) Image quality assessment for fused remote sensing imageries. Jurnal Teknologi, 71 (4). pp. 175-180. ISSN 0127-9696 http://dx.doi.org/10.11113/jt.v71.3839 DOI: 10.11113/jt.v71.3839 |
institution |
Universiti Teknologi Malaysia |
building |
UTM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Teknologi Malaysia |
content_source |
UTM Institutional Repository |
url_provider |
http://eprints.utm.my/ |
language |
English |
topic |
HD Industries. Land use. Labor |
spellingShingle |
HD Industries. Land use. Labor Md. Reba, Mohd. Nadzri C’uang, Ong Juey Image quality assessment for fused remote sensing imageries |
description |
Image fusion provides precise information in both spatial and spectral resolutions that benefit significantly in high accuracy mapping. Yet, there is less intention withdrawn in justifying the performance of the fused image. In this study, qualitative and quantitative assessments were carried out to test the quality of fusion image. Principal Component Analysis (PCA), Gram-Schmidt and Ehlers were applied to fuse the hyperspectral and Lidar image. Ehlers fusion showed good in preserving the color of image and contained the most information. Besides, the classification of Ehlers fused image showed the highest accuracy. |
format |
Article |
author |
Md. Reba, Mohd. Nadzri C’uang, Ong Juey |
author_facet |
Md. Reba, Mohd. Nadzri C’uang, Ong Juey |
author_sort |
Md. Reba, Mohd. Nadzri |
title |
Image quality assessment for fused remote sensing imageries |
title_short |
Image quality assessment for fused remote sensing imageries |
title_full |
Image quality assessment for fused remote sensing imageries |
title_fullStr |
Image quality assessment for fused remote sensing imageries |
title_full_unstemmed |
Image quality assessment for fused remote sensing imageries |
title_sort |
image quality assessment for fused remote sensing imageries |
publisher |
Penerbit UTM |
publishDate |
2014 |
url |
http://eprints.utm.my/id/eprint/53072/1/MohdNadzriMd2014_Imagequalityassessmentforfused.pdf http://eprints.utm.my/id/eprint/53072/ http://dx.doi.org/10.11113/jt.v71.3839 |
_version_ |
1643653298531598336 |