First Advisor

Bryant York

Term of Graduation

2009

Date of Publication

2009

Document Type

Thesis

Degree Name

Master of Science (M.S.) in Computer Science

Department

Computer Science

Language

English

Subjects

Outer planets -- Atmospheres, Image processing, Orthogonalization methods

DOI

10.15760/etd.2662

Physical Description

1 online resource (2, xii, 79 pages)

Abstract

The dynamic atmospheres of Jupiter, Saturn, Uranus, and Neptune provide a rich source of meteorological phenomena for scientists to study. To investigate these planets, scientists obtain spectral images of these bodies using various instruments including the Cooled Mid-Infrared Camera and Spectrometer (COMICS) at the Subaru Telescope Facility at Mauna Kea, Hawaii. These spectral images are two-dimensional arrays of double precision floating point values that have been read from a detector array. Such images must be reduced before the information they contain can be analyzed. The reduction process for spectral images from COMICS involves several steps:

1. Sky subtraction: the background radiation from Earth’s atmosphere must be subtracted from the spectral images.

2. Read-out pattern noise reduction: the noise related to reading data from detectors must be subtracted from the spectral images.

3. Division by the flat: the spectral images must be corrected for non-uniformities in the detector array response.

4. Orthogonalization: the spectral images must be transformed so that the images’ axes are perpendicular.

5. Extraction: individual spectra must be extracted from the spectral images. These spectra are plots of pixel intensity as a function of position along the x-axis of a spectral image.

6. Calibration: the x- and y- axes of the extracted spectra must be converted to units that are meaningful for scientific analysis.

In earlier work, the author developed software tools to support the first three steps in this reduction process. This thesis presents algorithms for performing the next two reduction steps, namely orthogonalization and extraction. More specifically, this thesis addresses the following research question: What are proper methods of orthogonalizing spectral images in preparation for extraction?

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Comments

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Persistent Identifier

https://archives.pdx.edu/ds/psu/16524

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