Abstract

The goal of this research was to develop an algorithm for identifying the constituent gases in stack releases. At the heart of the algorithm is a stepwise linear regression technique that only includes a basis vector in the model if it contributes significantly to the fit. This significance is calculated by an F-statistic. Issues such as atmospheric compensation, gas absorption and emission, background modeling, and fitting a linear regression to a non-linear radiance model were addressed in order to generate the matrix of basis vectors. Synthetic imagery generated by the DIRISG model were used as test cases. Results show that the ability to correctly identify a gas diminishes as a function of decreasing concentration path-length of the plume. Results drawn from pixels near the stack are more likely to give an accurate identification of the gas present in the plume.

Library of Congress Subject Headings

Remote sensing--Data processing; Gases--Spectra; Image processing--Digital techniques; Regression analysis

Publication Date

2005

Document Type

Thesis

Student Type

Graduate

Degree Name

Imaging Science (MS)

Department, Program, or Center

Chester F. Carlson Center for Imaging Science (COS)

Advisor

Carl Salvaggio

Advisor/Committee Member

John Schott

Advisor/Committee Member

David Messinger

Comments

Physical copy available from RIT's Wallace Library at TA1632 .P64 2005

Campus

RIT – Main Campus

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