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A study of 2-D phase unwrapping.

Ying, Lei.

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A study of 2-D phase unwrapping.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	A study of 2-D phase unwrapping./
作者:	Ying, Lei.
面頁冊數:	99 p.
附註:	Source: Dissertation Abstracts International, Volume: 64-03, Section: B, page: 1422.
Contained By:	Dissertation Abstracts International64-03B.
標題:	Engineering, Electronics and Electrical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3086223

A study of 2-D phase unwrapping.
Ying, Lei.

A study of 2-D phase unwrapping. - 99 p.

Source: Dissertation Abstracts International, Volume: 64-03, Section: B, page: 1422.

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2003.

Two-dimensional phase unwrapping arises most naturally in interferometric processing. Phase values from coherent multidimensional signals are related in a nonlinear manner to a desired physical quantity of interest. Due to 2π ambiguity, the measured or calculated phase is wrapped into the interval (−π, π]. Phase unwrapping generally is necessary to retrieve the physical quantity.Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

A study of 2-D phase unwrapping.
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245 1 0 $a A study of 2-D phase unwrapping.
300 $a 99 p.
500 $a Source: Dissertation Abstracts International, Volume: 64-03, Section: B, page: 1422.
500 $a Adviser: David C. Munson, Jr.
502 $a Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2003.
520 $a Two-dimensional phase unwrapping arises most naturally in interferometric processing. Phase values from coherent multidimensional signals are related in a nonlinear manner to a desired physical quantity of interest. Due to 2π ambiguity, the measured or calculated phase is wrapped into the interval (−π, π]. Phase unwrapping generally is necessary to retrieve the physical quantity.
520 $a Exciting applications have led to an explosive growth in research on phase unwrapping. It is well understood that 2-D phase unwrapping is an ill-posed inverse problem in general. Practical solutions tied to applications motivate most studies on this topic, including the work in this dissertation.
520 $a We begin by briefly reviewing existing techniques for 2-D phase unwrapping. We then propose a novel Bayesian approach to 2-D phase unwrapping. The phase is unwrapped according to a maximum a posteriori (MAP) rule, where the true phase is assumed to be a Markov random field. The estimate is made through a form of 2-D dynamic programming.
520 $a We analyze the performance of the approach by regarding phase unwrapping as decoding of a convolutional code. An upper bound for probability of pixel error is derived based on a Gaussian Markov random field model. Monte Carlo simulation results acquired using Gibbs sampling show the performance improves with increasing number of states. On the other hand, the computational complexity also increases. Several approaches using iterative processing are proposed to improve performance without examining a large number of states in the program. Different raster scans are adopted in consecutive iterations. Comparisons with the conventional least-square and branch-cut algorithms suggest that the improved algorithms are superior. The new approaches were also tested on real interferometric synthetic aperture radar (InSAR) data and magnetic resonance (MR) data and proven to work in these applications.
520 $a Finally, multibaseline phase unwrapping for InSAR processing is discussed. An MAP approach is proposed to overcome the drawbacks of the conventional maximum likelihood (ML) approach. The optimal choice of baselines is derived.
590 $a School code: 0090.
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