NDLI: Image reconstruction for air pollution based on passive FTIR with computed tomography

Content Provider	IEEE Xplore Digital Library
Author	Jing Fang Uezhi Yang
Copyright Year	2010
Description	Author affiliation: Lab. of Image Inf. Process., Hefei Univ. of Technol., Hefei, China (Jing Fang; Uezhi Yang)
Abstract	The image reconstruction method based on passive Fourier transform infrared (FTIR) coupled with computed tomography is presented in this paper: passive FTIR is used to obtain the path integral concentration of air pollution, combined with additive ART □ algorithm for reconstructing the two-dimensional distribution map of the air pollution. Detection principle, reconstruction algorithms, and optical telemetry structure design of the method is described in detail. A Gaussian function is applied to simulate the concentration distribution of polluting gases which spread at fixed point in the atmosphere. The concentration is reconstructed according to fan-beam geometry of passive FTIR The quality of the reconstruction image is assessed from the relative peak error, peak position error, and normalized mean square distance. It is discussed that the resolution is critical for the reconstruction quality: The final choice of grid resolution must balance accurate peak value reconstruction versus presence of pseudo-peaks. Based on this method, it is possible to reconstruct a complete concentration of air pollution, to locate the source emissions, and to accurately describe the process of their regional transmission.
Sponsorship	IEEE
Starting Page	2787
Ending Page	2793
File Size	429940
Page Count	7
File Format	PDF
ISBN	9781424465132
e-ISBN	9781424465163
DOI	10.1109/CISP.2010.5647593
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	computed tomography Atmospheric measurements passive FTIR Air pollution Pollution measurement image reconstruction Optical sensors algebraic reconstruction technology Image reconstruction Monitoring Pixel
Content Type	Text
Resource Type	Article

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