AN IMPROVED PULSE TRANSIENT AIRBORNE ELECTROMAGNETIC SYSTEM FOR LOCATING GOOD CONDUCTORS

Geophysics ◽  
1976 ◽  
Vol 41 (2) ◽  
pp. 287-299 ◽  
Author(s):  
D. Gupta Sarma ◽  
V. M. Maru ◽  
G. Varadarajan
Keyword(s):  
Comparative Study ◽  
Time Constant ◽  
Decay Time ◽  
Signal To Noise Ratio ◽  
Transient Field ◽  
Signal To Noise ◽  
Electromagnetic System ◽  
Airborne Electromagnetic ◽  
Expected Values ◽  
Noise Ratio

Measuring the transient field values (H), rather than their time derivatives (dH/dt), with an inductive, pulse‐excited electromagnetic prospecting system makes the device capable of reducing much of the geologic noise due to poor superficial conductors and enhancing the response from good conductors. The factor of improvement in signal‐to‐geologic noise ratio in H measurement may be as much as [Formula: see text], where [Formula: see text], and [Formula: see text] are the expected values of decay time constant of signal and noise components, respectively. Moreover, signal‐to‐noise ratio increases for later sample channels, thus allowing equal gate timings for all sample channels. Field results of a comparative study with H and dH/dt measurements are shown. It is predicted that both depth of exploration and reliability of interpretation of data in quantitative terms may improve somewhat with such a system.

Comparative Study on Filter Methods of Medical Ultrasound Images

2011 ◽  
Vol 341-342 ◽  
pp. 467-471
Author(s):  
Run Xia Ma ◽  
Xu Ming Zhang ◽  
Ming Yue Ding ◽  
Qi Liu
Keyword(s):  
Comparative Study ◽  
Gabor Filter ◽  
Signal To Noise Ratio ◽  
Median Filter ◽  
Minimum Mean Square Error ◽  
Ultrasound Image ◽  
Ultrasound Images ◽  
Signal To Noise ◽  
Protection Factor ◽  
Noise Ratio

This paper presents a comparative study on six despeckling methods such as modified hybrid median filter, gabor filter, speckle reducing anisotropic diffusion, homomorphic filter, non-local mean filter and squeeze box filter. We select eight objective evaluation parameters, such as signal-to-ratio, contrast signal–to–noise ratio, figure of merit, least absolute error, peak signal-to-noise ratio, edge protection factor, quantitative parameters of despeckling, signal-to-minimum mean square error ratio, to quantify the performance of these filters. The comparative study will provide a good guidance for selecting a suitable filter in the ultrasound image processing.

Resolution performance of Wiener filters

Geophysics ◽  
1983 ◽  
Vol 48 (7) ◽  
pp. 887-899 ◽  
Author(s):  
S. H. Bickel ◽  
D. R. Martinez
Keyword(s):  
Time Constant ◽  
Matched Filter ◽  
Signal To Noise Ratio ◽  
Wiener Filter ◽  
Resolving Power ◽  
General Definition ◽  
Resolution Time ◽  
Signal To Noise ◽  
Temporal Separation ◽  
Noise Ratio

To improve the resolution of seismic events, one often designs a Wiener inverse filter that optimally (in the least‐squares sense) transforms a measured source signature into a spike. When this filter is applied to seismic data, the bandwidth of any noise which is present increases along with the bandwidth of the signal. Thus the signal‐to‐noise ratio is degraded. To reduce signal ambiguity it is common practice to prewhiten the Wiener filter. Prewhitening the filter improves the output signal‐to‐ambient noise ratio, but at the same time it reduces resolution. The ability to resolve the temporal separation between events is determined by the resolution time constant which we define as the ratio of signal energy to peak signal power from the filter. For unfiltered wavelets the resolution time constant becomes the reciprocal of resolving power recently described by Widess (1982). For matched filter signals the resolution time constant can be regarded as the inverse of the frequency span of the signal. Although it is satisfying that the resolution time constant definition agrees with other measures of resolution, this more general definition has two major advantages. First, it incorporates the effect of filtering; second, it is easily generalized to incorporate the effects of noise by assuming that the filter is a Wiener filter. For a given amount of noise the Wiener filter is a generalization of the matched filter. Marine seismic wavelets demonstrate how reducing the noise level improves the resolution of a Wiener filter relative to a matched filter. For these wavelets a point of diminishing return is reached, such that, to realize a further small increase in resolution, a large increase in input signal‐to‐noise ratio is required to maintain interpretable information at the output.

scholarly journals Forensic Speaker Comparison Using Evidence Interval in Full Bayesian Significance Test

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Adelino P. Silva ◽  
Maurílio N. Vieira ◽  
Adriano V. Barbosa
Keyword(s):  
Monte Carlo ◽  
Markov Chains ◽  
Signal To Noise Ratio ◽  
Significance Test ◽  
Signal To Noise ◽  
Interval Size ◽  
Unknown Variance ◽  
Classification Errors ◽  
Expected Values ◽  
Noise Ratio

This paper describes the application of a full Bayesian significance test (FBST) to compute evidence intervals in forensic speaker comparison (FSC). In the FBST approach, the challenge is to apply the test to a large number of observations and to formulate an equation to solve the test quickly. The contribution of the present work is that it proposes an application of the FBST to FSC and develops a method to calculate the FBST for the distribution of expected values (mean) with unknown variance without using Monte Carlo Markov chains (MCMC). Comparisons with other interval inference methodologies indicate that the evidence interval size is 49% greater than that computed with the Gosset approach. The evidence interval presented 71% fewer classification errors than the punctual inference did for the signal-to-noise ratio (SNR) of 17 dB.

Determination of the Best Emulsion for the Microscopy of Crystals

1981 ◽  
Vol 39 ◽  
pp. 32-33
Author(s):  
David A. Grano ◽  
Kenneth H. Downing
Keyword(s):  
Spatial Frequency ◽  
Information Transfer ◽  
Signal To Noise Ratio ◽  
Experimental Situation ◽  
Photographic Emulsion ◽  
Modulation Transfer ◽  
Signal To Noise ◽  
Frequency Space ◽  
Noise Ratio

The retrieval of high-resolution information from images of biological crystals depends, in part, on the use of the correct photographic emulsion. We have been investigating the information transfer properties of twelve emulsions with a view toward 1) characterizing the emulsions by a few, measurable quantities, and 2) identifying the “best” emulsion of those we have studied for use in any given experimental situation. Because our interests lie in the examination of crystalline specimens, we've chosen to evaluate an emulsion's signal-to-noise ratio (SNR) as a function of spatial frequency and use this as our critereon for determining the best emulsion.The signal-to-noise ratio in frequency space depends on several factors. First, the signal depends on the speed of the emulsion and its modulation transfer function (MTF). By procedures outlined in, MTF's have been found for all the emulsions tested and can be fit by an analytic expression 1/(1+(S/S0)2). Figure 1 shows the experimental data and fitted curve for an emulsion with a better than average MTF. A single parameter, the spatial frequency at which the transfer falls to 50% (S0), characterizes this curve.

Experiments in Bright-Field Imaging with Hollow-Cone Illumination

1981 ◽  
Vol 39 ◽  
pp. 226-227
Author(s):  
W. Kunath ◽  
K. Weiss ◽  
E. Zeitler
Keyword(s):  
Signal To Noise Ratio ◽  
Carbon Support ◽  
Electronic System ◽  
Optic Axis ◽  
Hollow Cone ◽  
Signal To Noise ◽  
Bright Field ◽  
Noise Ratio ◽  
Single Field ◽  
Field Imaging

Bright-field images taken with axial illumination show spurious high contrast patterns which obscure details smaller than 15 ° Hollow-cone illumination (HCI), however, reduces this disturbing granulation by statistical superposition and thus improves the signal-to-noise ratio. In this presentation we report on experiments aimed at selecting the proper amount of tilt and defocus for improvement of the signal-to-noise ratio by means of direct observation of the electron images on a TV monitor.Hollow-cone illumination is implemented in our microscope (single field condenser objective, Cs = .5 mm) by an electronic system which rotates the tilted beam about the optic axis. At low rates of revolution (one turn per second or so) a circular motion of the usual granulation in the image of a carbon support film can be observed on the TV monitor. The size of the granular structures and the radius of their orbits depend on both the conical tilt and defocus.

Information capacity and bandwidth limitations in the SEM

1989 ◽  
Vol 47 ◽  
pp. 84-85
Author(s):  
D. C. Joy ◽  
R. D. Bunn
Keyword(s):  
Signal To Noise Ratio ◽  
Critical Dimension ◽  
Information Capacity ◽  
Acquisition Time ◽  
Signal To Noise ◽  
Sem Image ◽  
Probe Size ◽  
Minimum Number ◽  
Noise Ratio ◽  
Signal Channel

The information available from an SEM image is limited both by the inherent signal to noise ratio that characterizes the image and as a result of the transformations that it may undergo as it is passed through the amplifying circuits of the instrument. In applications such as Critical Dimension Metrology it is necessary to be able to quantify these limitations in order to be able to assess the likely precision of any measurement made with the microscope.The information capacity of an SEM signal, defined as the minimum number of bits needed to encode the output signal, depends on the signal to noise ratio of the image - which in turn depends on the probe size and source brightness and acquisition time per pixel - and on the efficiency of the specimen in producing the signal that is being observed. A detailed analysis of the secondary electron case shows that the information capacity C (bits/pixel) of the SEM signal channel could be written as :

Sign in / Sign up

Export Citation Format

Share Document