Abstract
Suspended atmospheric particles (particulate matter) are a form of air pollution that visually degrades urban scenery and is hazardous to human health and the environment. Current environmental monitoring devices are limited in their capability of measuring average particulate matter (PM) over large areas. Quantifying the visual effects of haze in digital images of urban scenery and correlating these effects to PM levels is a vital step in more practically monitoring our environment. Current image haze extraction algorithms remove all the haze from the scene and hence produce unnatural scenes for the sole purpose of enhancing vision. We present two algorithms which bridge the gap between image haze extraction and environmental monitoring. We provide a means of measuring atmospheric scattering from images of urban scenery by incorporating temporal knowledge. In doing so, we also present a method of recovering an accurate depthmap of the scene and recovering the scene without the visual effects of haze. We compare our algorithm to three known haze removal methods from the perspective of measuring atmospheric scattering, measuring depth and dehazing. The algorithms are composed of an optimization over a model of haze formation in images and an optimization using the constraint of constant depth over a sequence of images taken over time. These algorithms not only measure atmospheric scattering, but also recover a more accurate depthmap and dehazed image. The measurements of atmospheric scattering this research produces, can be directly correlated to PM levels and therefore pave the way to monitoring the health of the environment by visual means. Accurate atmospheric sensing from digital images is a challenging and under-researched problem. This work provides an important step towards a more practical and accurate visual means of measuring PM from digital images.
School
School of Sciences and Engineering
Department
Computer Science & Engineering Department
Degree Name
MS in Computer Science
Date of Award
6-1-2010
Online Submission Date
3-10-2013
First Advisor
Gluckman, Joshua
Committee Member 1
Gluckman, Joshua
Document Type
Thesis
Extent
121 p.
Rights
The American University in Cairo grants authors of theses and dissertations a maximum embargo period of two years from the date of submission, upon request. After the embargo elapses, these documents are made available publicly. If you are the author of this thesis or dissertation, and would like to request an exceptional extension of the embargo period, please write to thesisadmin@aucegypt.edu
IRB
Not necessary for this item
Recommended Citation
APA Citation
El-Gaaly, T.
(2010).Measuring atmospheric scattering from digital images of urban scenery using temporal polarization-based vision [Thesis, the American University in Cairo]. AUC Knowledge Fountain.
https://fount.aucegypt.edu/retro_etds/2319
MLA Citation
El-Gaaly, Tarek. Measuring atmospheric scattering from digital images of urban scenery using temporal polarization-based vision. 2010. American University in Cairo, Thesis. AUC Knowledge Fountain.
https://fount.aucegypt.edu/retro_etds/2319