Restoration of hazy satellite data based on spectral and statistical methods

Saiful Bahari, Nurul Iman and Ahmad, Asmala and Mohd Aboobaider, Burhanuddin and Sakidin, Hamzah and Razali, Muhammad Fahmi and Mohamad Isa, Mohd Saari (2016) Restoration of hazy satellite data based on spectral and statistical methods. ARPN Journal of Engineering and Applied Sciences, 11 (11). pp. 6807-6813. ISSN 1819-6608

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Abstract

Remote sensing data recorded from passive satellite system tend to be degraded by attenuation of solar radiation due to haze. Haze is capable of modifying the spectral and statistical properties of remote sensing data and consequently causes problem in data analysis and interpretation. Haze need to be removed or reduced in order to restore the quality of the data. In this study, initially, haze radiances due to radiation attenuation are removed by making use of pseudo invariant features (PIFs) selected among reflective objects within the study area. Spatial filters are subsequently used to remove the remaining noise causes by haze variability. The performance of hazy data restoration technique was evaluated by means of Support Vector Machine (SVM) classification. It is revealed that, the technique is able to improve the classification accuracy to the acceptable levels for data with moderate visibilities. Nevertheless, the technique is unable to do so for data with very low visibilities.

Item Type:	Article
Uncontrolled Keywords:	haze, landsat, support vector machine, spectral, statistical.
Subjects:	Q Science > Q Science (General) T Technology > T Technology (General)
Divisions:	Faculty of Information and Communication Technology > Department of Industrial Computing
Depositing User:	Dr. Asmala Ahmad
Date Deposited:	08 Aug 2016 07:48
Last Modified:	11 Jul 2023 11:49
URI:	http://eprints.utem.edu.my/id/eprint/16774
Statistic Details:	View Download Statistic

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