Haze Reduction from Remotely Sensed Data
Haze consists of atmospheric aerosols and molecules that scatter and absorb solar radiation, thus affecting the downward and upward solar radiance to be recorded by remote sensing sensors. Haze modifies the spectral signature of land classes and reduces classification accuracy, so causing problems t...
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Online Access: | http://eprints.utem.edu.my/id/eprint/12096/1/ahmadAMS33-36-2014_published.pdf http://eprints.utem.edu.my/id/eprint/12096/ http://www.m-hikari.com/ams/ams-2014/ams-33-36-2014/ahmadAMS33-36-2014.pdf http://dx.doi.org/10.12988/ams.2014.4289 |
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my.utem.eprints.120962015-05-28T04:22:23Z http://eprints.utem.edu.my/id/eprint/12096/ Haze Reduction from Remotely Sensed Data Asmala, A. Abd Ghani, M. K. Sazalinsyah, Razali Q Science (General) Haze consists of atmospheric aerosols and molecules that scatter and absorb solar radiation, thus affecting the downward and upward solar radiance to be recorded by remote sensing sensors. Haze modifies the spectral signature of land classes and reduces classification accuracy, so causing problems to users of remote sensing data. Hence, there is a need to reduce the haze effects to improve the usefulness of the data. A way to do this is by integrating spectral and statistical approaches. The result shows that the haze reduction method is able to increase the accuracy of the data statistically and visually. HIKARI LTD 2014 Article PeerReviewed application/pdf en http://eprints.utem.edu.my/id/eprint/12096/1/ahmadAMS33-36-2014_published.pdf Asmala, A. and Abd Ghani, M. K. and Sazalinsyah, Razali (2014) Haze Reduction from Remotely Sensed Data. Applied Mathematical Sciences, 8 (36). pp. 1755-1762. ISSN 1312-885X http://www.m-hikari.com/ams/ams-2014/ams-33-36-2014/ahmadAMS33-36-2014.pdf http://dx.doi.org/10.12988/ams.2014.4289 |
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Haze consists of atmospheric aerosols and molecules that scatter and absorb solar radiation, thus affecting the downward and upward solar radiance to be recorded by remote sensing sensors. Haze modifies the spectral signature of land classes and reduces classification accuracy, so causing problems to users of remote sensing data. Hence, there is a need to reduce the haze effects to improve the usefulness of the data. A way to do this is by integrating spectral and statistical approaches. The result shows that the haze reduction method is able to increase the accuracy of the data statistically and visually. |
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Article |
author |
Asmala, A. Abd Ghani, M. K. Sazalinsyah, Razali |
author_facet |
Asmala, A. Abd Ghani, M. K. Sazalinsyah, Razali |
author_sort |
Asmala, A. |
title |
Haze Reduction from Remotely Sensed Data |
title_short |
Haze Reduction from Remotely Sensed Data |
title_full |
Haze Reduction from Remotely Sensed Data |
title_fullStr |
Haze Reduction from Remotely Sensed Data |
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Haze Reduction from Remotely Sensed Data |
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haze reduction from remotely sensed data |
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HIKARI LTD |
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2014 |
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http://eprints.utem.edu.my/id/eprint/12096/1/ahmadAMS33-36-2014_published.pdf http://eprints.utem.edu.my/id/eprint/12096/ http://www.m-hikari.com/ams/ams-2014/ams-33-36-2014/ahmadAMS33-36-2014.pdf http://dx.doi.org/10.12988/ams.2014.4289 |
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