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Algorithm for haze determination using digital camera images
S. A. Hashim
School of Physics
Universiti Sains Malaysia, Malaysia
Email: syahamin@yahoo.com
M. Z. MatJafri
School of Physics
Universiti Sains Malaysia, Malaysia
Email: mjafri@usm.my
K. Abdullah
School of Physics
Universiti Sains Malaysia, Malaysia
Email: khirudd@usm.my
N. Mohd. Salleh
School of Physics
Universiti Sains Malaysia, Malaysia
M. N. Ariffin
School of Physics
Universiti Sains Malaysia, Malaysia
M. B. Abdul Wahab
School of Physics
Universiti Sains Malaysia, Malaysia
ABSTRACT
In this study, an algorithm was developed based on the atmospheric optical properties to determine the concentration of PM10 (particulate matter of size less than 10 micron). The objective of this study was to test digital camera images to determine the PM10 concentration in Penang Island, Malaysia. An algorithm for haze determination was developed based on the relationship between the measured reflectance and the reflected components from a surface material and the atmosphere. The Sony Cybershot digital camera was used to capture images of a dark target (black board) at near and far distances from the position of the target. Ground PM10 measurements were carried out at selected locations simultaneously during the digital camera images acquisition using a DustTrak™ meter. The PCI Geomatica version 9.1 digital image processing software was used in all image-processing analyses. The digital colour images were separated into three bands namely red, green and blue for multi-spectral analysis. The digital numbers (DN) for each band corresponding to the ground-truth locations were extracted and converted to radiance and reflectance values. The reflectance measured from the digital camera images was subtracted by the amount given by the surface reflectance to obtain the atmospheric reflectance. Then the atmospheric reflectance was related to the PM10 using the regression algorithm analysis. The proposed algorithm produced a high correlation coefficient (R) and low root-mean-square error (RMS) between the measured and estimated PM10. This indicates that the technique using the digital camera images can provide a useful tool for air quality studies.
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