Uncertainties of differential phase estimation associated with interferometric sonars

1996 ◽  
Vol 21 (1) ◽  
pp. 53-63 ◽  
Author(s):  
Guoliang Jin ◽  
Dajun Tang
Keyword(s):  
Phase Estimation ◽  
Differential Phase

Improving Time-Efficiency of Variational Specific Differential Phase Estimation

2020 ◽  
pp. 1-23
Author(s):  
Hao Huang ◽  
Kun Zhao ◽  
Haonan Chen ◽  
Gang Chen ◽  
Dongming Hu ◽  
...  
Keyword(s):  
Phase Estimation ◽  
Time Efficiency ◽  
Differential Phase

scholarly journals Differential phase estimation with the SeaMARCII bathymetric sidescan sonar system

1992 ◽  
Vol 17 (3) ◽  
pp. 239-251 ◽  
Author(s):  
M.A. Masnadi-Shirazi ◽  
C. de Moustier ◽  
P. Cervenka ◽  
S.H. Zisk
Keyword(s):  
Sidescan Sonar ◽  
Phase Estimation ◽  
Differential Phase ◽  
Sonar System

The role of differential phase contrast in electron microscopy

1978 ◽  
Vol 36 (1) ◽  
pp. 176-177
Author(s):  
E.M. Waddell ◽  
J.N. Chapman ◽  
R.P. Ferrier
Keyword(s):  
Phase Contrast ◽  
Practical Method ◽  
Position Vector ◽  
Differential Phase ◽  
Pure Phase ◽  
Differential Phase Contrast ◽  
The Difference ◽  
Image Position ◽  
First Moment

Dekkers and de Lang (1977) have discussed a practical method of realising differential phase contrast in a STEM. The method involves taking the difference signal from two semi-circular detectors placed symmetrically about the optic axis and subtending the same angle (2α) at the specimen as that of the cone of illumination. Such a system, or an obvious generalisation of it, namely a quadrant detector, has the characteristic of responding to the gradient of the phase of the specimen transmittance. In this paper we shall compare the performance of this type of system with that of a first moment detector (Waddell et al.1977).For a first moment detector the response function R(k) is of the form R(k) = ck where c is a constant, k is a position vector in the detector plane and the vector nature of R(k)indicates that two signals are produced. This type of system would produce an image signal given bywhere the specimen transmittance is given by a (r) exp (iϕ (r), r is a position vector in object space, ro the position of the probe, ⊛ represents a convolution integral and it has been assumed that we have a coherent probe, with a complex disturbance of the form b(r-ro) exp (iζ (r-ro)). Thus the image signal for a pure phase object imaged in a STEM using a first moment detector is b2 ⊛ ▽ø. Note that this puts no restrictions on the magnitude of the variation of the phase function, but does assume an infinite detector.

Resolution assessment from spectral signal-to-noise ratios

1987 ◽  
Vol 45 ◽  
pp. 746-747
Author(s):  
M. Unser ◽  
B.L. Trus ◽  
A.C. Steven
Keyword(s):  
Electron Microscopy ◽  
Limiting Factor ◽  
Biological Macromolecules ◽  
Signal To Noise ◽  
Differential Phase ◽  
Traditional Measure ◽  
Spectral Signal ◽  
Two Measures ◽  
Diffraction Patterns ◽  
Averaging Techniques

Since the resolution-limiting factor in electron microscopy of biological macromolecules is not instrumental, but is rather the preservation of structure, operational definitions of resolution have to be based on the mutual consistency of a set of like images. The traditional measure of resolution for crystalline specimens in terms of the extent of periodic reflections in their diffraction patterns is such a criterion. With the advent of correlation averaging techniques for lattice rectification and the analysis of non-crystalline specimens, a more general - and desirably, closely compatible - resolution criterion is needed. Two measures of resolution for correlation-averaged images have been described, namely the differential phase residual (DPR) and the Fourier ring correlation (FRC). However, the values that they give for resolution often differ substantially. Furthermore, neither method relates in a straightforward way to the long-standing resolution criterion for crystalline specimens.

An Absolute Phase Estimation Method for Interferometry Imagery

2019 ◽  
Vol 1 (2) ◽  
pp. 14-19
Author(s):  
Sui Ping Lee ◽  
Yee Kit Chan ◽  
Tien Sze Lim
Keyword(s):  
Noise Suppression ◽  
Estimation Method ◽  
Phase Image ◽  
Phase Estimation ◽  
Phase Reconstruction ◽  
Estimation Algorithms ◽  
Absolute Phase ◽  
Filtering Rate ◽  
Interferometric Phase ◽  
Image Performance

Accurate interpretation of interferometric image requires an extremely challenging task based on actual phase reconstruction for incomplete noise observation. In spite of the establishment of comprehensive solutions, until now, a guaranteed means of solution method is yet to exist. The initially observed interferometric image is formed by 2π-periodic phase image that wrapped within (-π, π]. Such inverse problem is further corrupted by noise distortion and leads to the degradation of interferometric image. In order to overcome this, an effective algorithm that enables noise suppression and absolute phase reconstruction of interferometric phase image is proposed. The proposed method incorporates an improved order statistical filter that is able to adjust or vary on its filtering rate by adapting to phase noise level of relevant interferometric image. Performance of proposed method is evaluated and compared with other existing phase estimation algorithms. The comparison is based on a series of computer simulated and real interferometric data images. The experiment results illustrate the effectiveness and competency of the proposed method.

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