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Assessment of Multi-Temporal Image Fusion for Remote Sensing Application

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@article{IJASEIT1676,
   author = {- Yuhendra and Joshapat Tetuko Sri Sumantyo},
   title = {Assessment of Multi-Temporal Image Fusion  for Remote Sensing Application},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {7},
   number = {3},
   year = {2017},
   pages = {778--784},
   keywords = {multi-sensor; multi-temporal fusion; component substitution; multi-resolution analysis},
   abstract = {Image fusion and subsequent scene analysis are important for studying Earth surface conditions from remotely sensed imagery. The fusion of the same scene using satellite data taken with different sensors or acquisition times is known as multi-sensor or multi-temporal fusion, respectively. The purpose of this study is to investigate the effects of misalignments the multi-sensor, multi-temporal fusion process when a pan-sharpened scene is produced from low spatial resolution multispectral (MS) images and a high spatial resolution panchromatic (PAN) image. It is found that the component substitution (CS) fusion method provides better performance than the multi-resolution analysis (MRA) scheme. Quantitative analysis shows that the CS-based method gives a better result in terms of spatial quality (sharpness), whereas the MRA-based method yields better spectral quality, i.e., better color fidelity to the original MS images.},
   issn = {2088-5334},
   publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},
   url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1676},
   doi = {10.18517/ijaseit.7.3.1676}
}

EndNote

%A Yuhendra, -
%A Sri Sumantyo, Joshapat Tetuko
%D 2017
%T Assessment of Multi-Temporal Image Fusion  for Remote Sensing Application
%B 2017
%9 multi-sensor; multi-temporal fusion; component substitution; multi-resolution analysis
%! Assessment of Multi-Temporal Image Fusion  for Remote Sensing Application
%K multi-sensor; multi-temporal fusion; component substitution; multi-resolution analysis
%X Image fusion and subsequent scene analysis are important for studying Earth surface conditions from remotely sensed imagery. The fusion of the same scene using satellite data taken with different sensors or acquisition times is known as multi-sensor or multi-temporal fusion, respectively. The purpose of this study is to investigate the effects of misalignments the multi-sensor, multi-temporal fusion process when a pan-sharpened scene is produced from low spatial resolution multispectral (MS) images and a high spatial resolution panchromatic (PAN) image. It is found that the component substitution (CS) fusion method provides better performance than the multi-resolution analysis (MRA) scheme. Quantitative analysis shows that the CS-based method gives a better result in terms of spatial quality (sharpness), whereas the MRA-based method yields better spectral quality, i.e., better color fidelity to the original MS images.
%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1676
%R doi:10.18517/ijaseit.7.3.1676
%J International Journal on Advanced Science, Engineering and Information Technology
%V 7
%N 3
%@ 2088-5334

IEEE

- Yuhendra and Joshapat Tetuko Sri Sumantyo,"Assessment of Multi-Temporal Image Fusion  for Remote Sensing Application," International Journal on Advanced Science, Engineering and Information Technology, vol. 7, no. 3, pp. 778-784, 2017. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.7.3.1676.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Yuhendra, -
AU  - Sri Sumantyo, Joshapat Tetuko
PY  - 2017
TI  - Assessment of Multi-Temporal Image Fusion  for Remote Sensing Application
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 7 (2017) No. 3
Y2  - 2017
SP  - 778
EP  - 784
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - multi-sensor; multi-temporal fusion; component substitution; multi-resolution analysis
N2  - Image fusion and subsequent scene analysis are important for studying Earth surface conditions from remotely sensed imagery. The fusion of the same scene using satellite data taken with different sensors or acquisition times is known as multi-sensor or multi-temporal fusion, respectively. The purpose of this study is to investigate the effects of misalignments the multi-sensor, multi-temporal fusion process when a pan-sharpened scene is produced from low spatial resolution multispectral (MS) images and a high spatial resolution panchromatic (PAN) image. It is found that the component substitution (CS) fusion method provides better performance than the multi-resolution analysis (MRA) scheme. Quantitative analysis shows that the CS-based method gives a better result in terms of spatial quality (sharpness), whereas the MRA-based method yields better spectral quality, i.e., better color fidelity to the original MS images.
UR  - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1676
DO  - 10.18517/ijaseit.7.3.1676

RefWorks

RT Journal Article
ID 1676
A1 Yuhendra, -
A1 Sri Sumantyo, Joshapat Tetuko
T1 Assessment of Multi-Temporal Image Fusion  for Remote Sensing Application
JF International Journal on Advanced Science, Engineering and Information Technology
VO 7
IS 3
YR 2017
SP 778
OP 784
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 multi-sensor; multi-temporal fusion; component substitution; multi-resolution analysis
AB Image fusion and subsequent scene analysis are important for studying Earth surface conditions from remotely sensed imagery. The fusion of the same scene using satellite data taken with different sensors or acquisition times is known as multi-sensor or multi-temporal fusion, respectively. The purpose of this study is to investigate the effects of misalignments the multi-sensor, multi-temporal fusion process when a pan-sharpened scene is produced from low spatial resolution multispectral (MS) images and a high spatial resolution panchromatic (PAN) image. It is found that the component substitution (CS) fusion method provides better performance than the multi-resolution analysis (MRA) scheme. Quantitative analysis shows that the CS-based method gives a better result in terms of spatial quality (sharpness), whereas the MRA-based method yields better spectral quality, i.e., better color fidelity to the original MS images.
LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1676
DO  - 10.18517/ijaseit.7.3.1676