Information reduction in holograms by superimposing spatial frequency bands

2003 ◽  
Author(s):  
Satoshi Nakazaki ◽  
Kunihiro Sato ◽  
Masakazu Morimoto ◽  
Kensaku Fujii
Author(s):  
Payel Ghosh ◽  
Sarad Subhra S. Bhakat ◽  
Ipsita Chakraborty ◽  
Sanjukta Sarkar ◽  
Kallol Bhattacharya

Perception ◽  
1997 ◽  
Vol 26 (8) ◽  
pp. 1011-1025 ◽  
Author(s):  
David J Tolhurst ◽  
Yoav Tadmor

Thresholds were measured for discriminating changes in the slopes of the amplitude spectra of stimuli derived from photographs of natural scenes and from random-luminance patterns. The variety and magnitudes of the thresholds could be explained by a model based on the discrimination of the changes in band-limited local contrast. Different spatial scales of local contrast (or different spatial-frequency bands of about 1 octave) were implicated for different reference spectral slopes; the model implicated a lower frequency-band for stimuli with shallower amplitude spectra. The implications of the model were tested experimentally by using stimuli in which the spectra were changed within restricted spatial-frequency bands. When the amplitude spectra of the test and reference stimuli differed only within the implicated frequency bands, thresholds were affected little. However, when the test and reference spectra differed at all frequencies except those in the implicated bands, the thresholds were elevated markedly. The forms of the psychometric functions for the discrimination task were entirely compatible with the hypothesis that the task relies upon the ability to discriminate changes of contrast. The Weibull functions fitted to the data had slope parameters (β) in the range 1 to 3, compatible with discrimination of low (but suprathreshold) contrasts.


Author(s):  
Vanitha Kamarthi ◽  
D. Satyanarayana ◽  
M.N. Giri Prasad

Background: Image fusion has been grown as an effectual method in diseases related diagnosis schemes. Methods: In this paper, a new method for combining multimodal medical images using spatial frequency motivated parameter-adaptive PCNN (SF-PAPCNN) is suggested. The multi-modal images are disintegrated into frequency bands by using decomposition NSST. The coefficients of low frequency bands are selected using maximum rule. The coefficients of high frequency bands are combined by SF-PAPCNN. Results: The fused medical images is obtained by applying INSST to above coefficients. Conclusion: The quality metrics such as entropy ENT, fusion symmetry FS, deviation STD, mutual information QMI and edge strength QAB/F are used to validate the efficacy of suggested scheme.


2010 ◽  
Vol 10 (10) ◽  
pp. 25-25 ◽  
Author(s):  
P. Rotshtein ◽  
A. Schofield ◽  
M. J. Funes ◽  
G. W. Humphreys

2010 ◽  
Vol 9 (8) ◽  
pp. 806-806
Author(s):  
P. Rotshtein ◽  
A. Schofield ◽  
M. J. Funes ◽  
G. W. Humphreys

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.


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