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Reconstruction of irregularly sample...

Tian, Jialin.

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Reconstruction of irregularly sampled interferograms in imaging Fourier transform spectrometry.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Reconstruction of irregularly sampled interferograms in imaging Fourier transform spectrometry./
作者:	Tian, Jialin.
面頁冊數:	156 p.
附註:	Source: Dissertation Abstracts International, Volume: 65-03, Section: B, page: 1482.
Contained By:	Dissertation Abstracts International65-03B.
標題:	Engineering, Electronics and Electrical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3126743
ISBN:	0496740210

Reconstruction of irregularly sampled interferograms in imaging Fourier transform spectrometry.
Tian, Jialin.

Reconstruction of irregularly sampled interferograms in imaging Fourier transform spectrometry. - 156 p.

Source: Dissertation Abstracts International, Volume: 65-03, Section: B, page: 1482.

Thesis (Ph.D.)--Georgia Institute of Technology, 2004.

A common problem that exists in FTS is concerned with how to compensate for sampling errors when an interferogram is sampled at nonuniform instants in the path-difference domain. These errors, due to various mechanical irregularities, are generally associated with a continuous scanning system, which samples the interferogram at either equal space or equal time intervals. In both systems, the accuracy of the reconstructed signal can be significantly compromised if no error correction is performed. In addition, if the nonuniform sampling locations are unknown, which is the case when a laser reference is not present, the reconstruction algorithm must be able to correct the sampling errors "blindly." The current technique for solving this problem in the FTS industry involves a low-pass interpolation/resampling process, which only has been applied to a single detector problem, and it does not offer a solution when sampling locations are unknown.

ISBN: 0496740210Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

Reconstruction of irregularly sampled interferograms in imaging Fourier transform spectrometry.
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502 $a Thesis (Ph.D.)--Georgia Institute of Technology, 2004.
520 $a A common problem that exists in FTS is concerned with how to compensate for sampling errors when an interferogram is sampled at nonuniform instants in the path-difference domain. These errors, due to various mechanical irregularities, are generally associated with a continuous scanning system, which samples the interferogram at either equal space or equal time intervals. In both systems, the accuracy of the reconstructed signal can be significantly compromised if no error correction is performed. In addition, if the nonuniform sampling locations are unknown, which is the case when a laser reference is not present, the reconstruction algorithm must be able to correct the sampling errors "blindly." The current technique for solving this problem in the FTS industry involves a low-pass interpolation/resampling process, which only has been applied to a single detector problem, and it does not offer a solution when sampling locations are unknown.
520 $a When sampling positions are available, two alternatives are presented in this thesis. The first method recovers the data using a truncated "sinc" interpolation, whereas the second method solves the problem using a linear interpolation based on the interferogram's symmetry property. Each algorithm has its own unique strength: the linear interpolation method is easy to implement, highly efficient, and is able to produce exceptionally accurate results under low-noise conditions; the "sinc" interpolation method is more robust to noise, and is capable of controlling the output quality through an adjustable truncation window length.
520 $a In the case where sampling locations are unknown, an optimization problem with multiple objective and constraint functions is designed based on the spatial and spectral characteristics of the data measurement. This problem is solved using an evolutionary approach, in which potential solutions are competing to be the fittest individual in a simulated natural environment. Two evolutionary algorithms are developed and compared to obtain the most desirable solution in the reconstruction without reference case. One of which emphasizes the estimation of sampling offsets while the other attempts to recover the actual values of all correct samples. The extensions of these algorithms are made to solve the multi-dimensional array problem.
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