Optical SAR Images Fusion: Comparative Analysis of Resulting Images Data

Image fusion is a useful tool for integrating low spatial resolution multispectral (MS) images with a high spatial resolution panchromatic (PAN) image, thus producing a high resolution multispectral image for better understanding of the observed earth surface. A main proposed the research were the e...

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Main Authors: Yuhendra, Minarni
Format: Article
Language:English
Published: EDP Sciences 2018-01-01
Series:MATEC Web of Conferences
Online Access:https://doi.org/10.1051/matecconf/201821501002
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spelling doaj-bc9cfd7a2b984793a8ecc6e3cf14f15b2021-02-02T07:15:11ZengEDP SciencesMATEC Web of Conferences2261-236X2018-01-012150100210.1051/matecconf/201821501002matecconf_ictis2018_01002Optical SAR Images Fusion: Comparative Analysis of Resulting Images DataYuhendraMinarniImage fusion is a useful tool for integrating low spatial resolution multispectral (MS) images with a high spatial resolution panchromatic (PAN) image, thus producing a high resolution multispectral image for better understanding of the observed earth surface. A main proposed the research were the effectiveness of different image fusion methods while filtering methods added to speckle suppression in synthetic aperture radar (SAR) images. The quality assessment of the filtering fused image implemented by statistical parameter namely mean, standard deviation, bias, universal index quality image (UIQI) and root mean squared error (RMSE). In order to test the robustness of the image quality, either speckle noise (Gamma map filter) is intentionally added to the fused image. When comparing and testing result, Gram Scmidth (GS) methods have shown better results for good colour reproduction, as compared with high pass filtering (HPF). And the other hands, GS, and wavelet intensity hue saturation (W-IHS) have shown the preserving good colour with original image for Landsat TM data.https://doi.org/10.1051/matecconf/201821501002
collection DOAJ
language English
format Article
sources DOAJ
author Yuhendra
Minarni
spellingShingle Yuhendra
Minarni
Optical SAR Images Fusion: Comparative Analysis of Resulting Images Data
MATEC Web of Conferences
author_facet Yuhendra
Minarni
author_sort Yuhendra
title Optical SAR Images Fusion: Comparative Analysis of Resulting Images Data
title_short Optical SAR Images Fusion: Comparative Analysis of Resulting Images Data
title_full Optical SAR Images Fusion: Comparative Analysis of Resulting Images Data
title_fullStr Optical SAR Images Fusion: Comparative Analysis of Resulting Images Data
title_full_unstemmed Optical SAR Images Fusion: Comparative Analysis of Resulting Images Data
title_sort optical sar images fusion: comparative analysis of resulting images data
publisher EDP Sciences
series MATEC Web of Conferences
issn 2261-236X
publishDate 2018-01-01
description Image fusion is a useful tool for integrating low spatial resolution multispectral (MS) images with a high spatial resolution panchromatic (PAN) image, thus producing a high resolution multispectral image for better understanding of the observed earth surface. A main proposed the research were the effectiveness of different image fusion methods while filtering methods added to speckle suppression in synthetic aperture radar (SAR) images. The quality assessment of the filtering fused image implemented by statistical parameter namely mean, standard deviation, bias, universal index quality image (UIQI) and root mean squared error (RMSE). In order to test the robustness of the image quality, either speckle noise (Gamma map filter) is intentionally added to the fused image. When comparing and testing result, Gram Scmidth (GS) methods have shown better results for good colour reproduction, as compared with high pass filtering (HPF). And the other hands, GS, and wavelet intensity hue saturation (W-IHS) have shown the preserving good colour with original image for Landsat TM data.
url https://doi.org/10.1051/matecconf/201821501002
work_keys_str_mv AT yuhendra opticalsarimagesfusioncomparativeanalysisofresultingimagesdata
AT minarni opticalsarimagesfusioncomparativeanalysisofresultingimagesdata
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