Optimization of the exposure time of aerospace camera through its signal-to-noise ratio

Author(s):  
Yuheng Chen ◽  
Yiqun Ji ◽  
Jiankang Zhou ◽  
Xinhua Chen ◽  
Weimin Shen
1988 ◽  
Vol 132 ◽  
pp. 35-38
Author(s):  
Dennis C. Ebbets ◽  
Sara R. Heap ◽  
Don J. Lindler

The G-HRS is one of four axial scientific instruments which will fly aboard the Hubble Space Telescope (ref 1,2). It will produce spectroscopic observations in the 1050 A ≤ λ ≤ 3300 A region with greater spectral, spatial and temporal resolution than has been possible with previous space-based instruments. Five first order diffraction gratings and one Echelle provide three modes of spectroscopic operation with resolving powers of R = λ/ΔΔ = 2000, 20000 and 90000. Two magnetically focused, pulse-counting digicon detectors, which differ only in the nature of their photocathodes, produce data whose photometric quality is usually determined by statistical noise in the signal (ref 3). Under ideal circumstances the signal to noise ratio increases as the square root of the exposure time. For some observations detector dark count, instrumental scattered light or granularity in the pixel to pixel sensitivity will cause additional noise. The signal to noise ratio of the net spectrum will then depend on several parameters, and will increase more slowly with exposure time. We have analyzed data from the ground based calibration programs, and have developed a theoretical model of the HRS performance (ref 4). Our results allow observing and data reduction strategies to be optimized when factors other than photon statistics influence the photometric quality of the data.


1994 ◽  
Vol 38 ◽  
pp. 691-698
Author(s):  
K. Kansai ◽  
K. Toda ◽  
H. Kohno ◽  
T. Arai ◽  
R. Wilson

Advancements in trace clement analysis require improvements in both the signal-to-noise ratio and accurate background correction. With a sequential spectrometer, one can obtain detection limits of around 0.1 ppm for medium to heavy Z elements. Conditions can be individually optimized for each element, for example, selection of filters, collimators, crystals and background subtraction. The disadvantage is that the analysis time may become “long” if many elements are to be analyzed. This long exposure time can lead to the deterioration of some samples.


1979 ◽  
Vol 50 ◽  
pp. 25-1-25-24 ◽  
Author(s):  
J.G. Walker

AbstractThe dependence of the signal to noise ratio on the exposure parameters in speckle interferometry is analysed. The choice of the optimum exposure parameters, which are found to depend on certain statistical functions of the image intensity, is discussed. Preliminary results of measurements of these statistical functions are given.


Author(s):  
David A. Grano ◽  
Kenneth H. Downing

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.


Author(s):  
W. Kunath ◽  
K. Weiss ◽  
E. Zeitler

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.


Author(s):  
D. C. Joy ◽  
R. D. Bunn

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 :


1979 ◽  
Vol 10 (4) ◽  
pp. 221-230 ◽  
Author(s):  
Veronica Smyth

Three hundred children from five to 12 years of age were required to discriminate simple, familiar, monosyllabic words under two conditions: 1) quiet, and 2) in the presence of background classroom noise. Of the sample, 45.3% made errors in speech discrimination in the presence of background classroom noise. The effect was most marked in children younger than seven years six months. The results are discussed considering the signal-to-noise ratio and the possible effects of unwanted classroom noise on learning processes.


2020 ◽  
Vol 63 (1) ◽  
pp. 345-356
Author(s):  
Meital Avivi-Reich ◽  
Megan Y. Roberts ◽  
Tina M. Grieco-Calub

Purpose This study tested the effects of background speech babble on novel word learning in preschool children with a multisession paradigm. Method Eight 3-year-old children were exposed to a total of 8 novel word–object pairs across 2 story books presented digitally. Each story contained 4 novel consonant–vowel–consonant nonwords. Children were exposed to both stories, one in quiet and one in the presence of 4-talker babble presented at 0-dB signal-to-noise ratio. After each story, children's learning was tested with a referent selection task and a verbal recall (naming) task. Children were exposed to and tested on the novel word–object pairs on 5 separate days within a 2-week span. Results A significant main effect of session was found for both referent selection and verbal recall. There was also a significant main effect of exposure condition on referent selection performance, with more referents correctly selected for word–object pairs that were presented in quiet compared to pairs presented in speech babble. Finally, children's verbal recall of novel words was statistically better than baseline performance (i.e., 0%) on Sessions 3–5 for words exposed in quiet, but only on Session 5 for words exposed in speech babble. Conclusions These findings suggest that background speech babble at 0-dB signal-to-noise ratio disrupts novel word learning in preschool-age children. As a result, children may need more time and more exposures of a novel word before they can recognize or verbally recall it.


Author(s):  
Yu ZHOU ◽  
Wei ZHAO ◽  
Zhixiong CHEN ◽  
Weiqiong WANG ◽  
Xiaoni DU

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