scholarly journals The modulation transfer function and signal-to-noise ratio of different digital filters: a technical approach

2011 ◽  
Vol 40 (4) ◽  
pp. 222-229 ◽  
Author(s):  
DD Brüllmann ◽  
B d'Hoedt
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.


2018 ◽  
Vol 57 (9) ◽  
pp. 616-625 ◽  
Author(s):  
Tatiana Monaretto ◽  
Andre Souza ◽  
Tiago Bueno Moraes ◽  
Victor Bertucci-Neto ◽  
Corinne Rondeau-Mouro ◽  
...  

2006 ◽  
Vol 18 (1) ◽  
pp. 26-44 ◽  
Author(s):  
Paul T. Clark ◽  
Mark C. W. van Rossum

The sparsity of photons at very low light levels necessitates a nonlinear synaptic transfer function between the rod photoreceptors and the rod-bipolar cells. We examine different ways to characterize the performance of the pathway: the error rate, two variants of the mutual information, and the signal-to-noise ratio. Simulation of the pathway shows that these approaches yield substantially different performance at very low light levels and that maximizing the signal-to-noise ratio yields the best performance when judged from simulated images. The results are compared to recent data.


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