Results 161 to 170 of about 4,791 (204)

Phase Unwrapping Algorithms: A Comparison

2000
Over the last few years a great deal of work has been done to improve the reliability of phase unwrapping algorithms. Many articles are to be found in the technical literature claiming the robustness and noise immunity of the proposed algorithm.
BALDI, ANTONIO, BERTOLINO, FILIPPO, GINESU, FRANCESCO   +2 more
openaire   +2 more sources

Phase Unwrapping for Magnetic Resonance Thermometry

2001
Magnetic resonance thermometry enables temperature measurement in a noninvasive way. A representation oft he temperature is given by the phase shift ofthe MR signal[1]. Unfortunately, only “wrapped phase” is measured directly, yielding values between -π and +π. However only the true phase(“unwrapped phase”) is proportional to temperature.
Suprijanto, -, Vos, FM, Vogel, MW (M.), Vossepoel, AM, Vrooman, Henri   +4 more
openaire   +2 more sources

Phase unwrapping by blocks

Measurement, 1999
Abstract A method of 2-dimensional phase-unwrapping by blocks is presented in this paper. This method combines the advantages of both conventional phase-unwrapping algorithm and cellular-automata unwrapping algorithm. With this concept, a fast, robust and stable phase unwrapping for phase maps of different sizes can be achieved by utilising different
Boxiong Wang, Yuqing Shi, T. Pfeifer, H. Mischo   +3 more
openaire   +1 more source

Phase unwrapping with a regularized phase-tracking system

Applied Optics, 1998
We develop a regularized phase-tracking (RPT) technique tounwrap phase maps. The phase maps that can be unwrapped with thisnew method may be bounded by arbitrarily shaped boundaries. Moreover, the RPT unwrapper has a higher noise robustness than previously reported phase-unwrapping schemes.
M, Servin, J L, Marroquin, D, Malacara, F J, Cuevas   +3 more
openaire   +2 more sources

Phase difference-based multichannel phase unwrapping

IEEE Transactions on Image Processing, 2005
This work addresses the derivation of the phase difference-based maximum likelihood (ML) phase unwrapping algorithm. To this end, we derive the joint statistics of the phase differences on a two-dimensional grid for the multichannel case, where several scaled wrapped phase values are available.
Fornaro G, Pauciullo A, Sansosti E
openaire   +4 more sources

Phase unwrapping by factorization

IEEE Transactions on Acoustics, Speech, and Signal Processing, 1982
An algorithm for the numerical factorization of very high degree but well-conditioned polynomials is developed. This is used to factor the z- transform of finite-length signals, and the zeros are used to calculate the unwrapped phase. The method has been tested on signals up to 512 points in length.
Steiglitz, Kenneth, Dickinson, Bradley
openaire   +1 more source

Phase difference based multiple acquisition phase unwrapping

IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477), 2004
This work addresses the derivation of a phase-difference (gradient) based maximum likelihood (ML) phase unwrapping algorithm. In particular, we determine and study the structure of the ML phase unwrapping on a 2D grid in the multi-channel case and compare it with existing phase unwrapping algorithms.
Fornaro G, Pauciullo A, Sansosti E
openaire   +3 more sources

Polynomial Phase Estimation by Least Squares Phase Unwrapping

IEEE Transactions on Signal Processing, 2014
Estimating the coefficients of a noisy polynomial phase signal is important in fields including radar, biology and radio communications. One approach attempts to perform polynomial regression on the phase of the signal. This is complicated by the fact that the phase is wrapped modulo 2π and must be unwrapped before regression can be performed.
Robby G. McKilliam, Barry G. Quinn, I. Vaughan L. Clarkson, William Moran 0001, Badri N. Vellambi   +4 more
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Robust audio localization with phase unwrapping

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017
Most of multichannel sound source Direction Of Arrival (DOA) estimation algorithms suffer from spatial aliasing problems. The phase differences between a pair of microphones are wrapped beyond the spatial aliasing frequency. A common solution is to adjust the distance between the microphones to obtain a suitable aliasing frequency, and take only the ...
Kainan Chen, Jürgen T. Geiger, Walter Kellermann   +2 more
openaire   +1 more source

Interface propagation method in phase unwrapping

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016
Path following algorithms employ information from phase residues or data quality, typically in a independent mode for the difference between the distribution discreteness of residues and the distribution continuity of data quality values. Residues are taken as sources for interface propagation, and the quality of phase data weigh against the ...
Jian Gao 0019, Jun Li, Lei Shi
openaire   +1 more source