Restoration of hazy data based on spectral and statistical methods

Saiful Bahari, N.i. and Ahmad, A. and Aboobaider, B.M. and Razali, M.F. and Sakidin, H. and Mohamad Isa, M.S. (2016) Restoration of hazy data based on spectral and statistical methods. ARPN Journal of Engineering and Applied Sciences, 11 (11). pp. 6807-6813.

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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 needs 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 accuracy. 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. © 2006-2016 Asian Research Publishing Network (ARPN).

Item Type:Article
Impact Factor:cited By 0
ID Code:25620
Deposited By: Ms Sharifah Fahimah Saiyed Yeop
Deposited On:27 Aug 2021 10:00
Last Modified:27 Aug 2021 10:00

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