Joint transform correlator based on off-focus inputting and spherical wave illuminating power spectrum

2012 ◽  
Vol 285 (24) ◽  
pp. 4931-4936
Author(s):  
Xiaopeng Deng ◽  
Xixiang Zhu ◽  
Wei Wen
Keyword(s):  
Power Spectrum ◽  
Spherical Wave ◽  
Joint Transform Correlator

Evaluation of a suitable threshold for binarization of power spectrum in a noise-free joint transform correlator

1992 ◽  
Vol 90 (4-6) ◽  
pp. 221-226 ◽  
Author(s):  
Santiago Vallmitjana ◽  
Ignacio Juvells ◽  
Arturo Carnicer
Keyword(s):  
Power Spectrum ◽  
Joint Transform Correlator

Improved Method of Target Detection on Optoelectronic Hybrid Joint Transform Correlator in Cluttered Scences

2011 ◽  
Vol 130-134 ◽  
pp. 4041-4044
Author(s):  
Yi Xian Qian ◽  
Li Bao Yang ◽  
Xiao Wei Cheng ◽  
Xue Ting Hong
Keyword(s):  
Fourier Transform ◽  
Power Spectrum ◽  
Inverse Fourier Transform ◽  
Zero Order ◽  
Reference Image ◽  
Improved Method ◽  
Joint Transform Correlator ◽  
Correlation Peak ◽  
Detection Ability ◽  
Large Correlation

A classical joint transform correlator (JTC) usually yields large correlation sidelobes as well as a large correlation peak width, strong zero-order peak, and low diffraction efficiency, which make the detection ability of JTC lower. To overcome these difficulties, firstly, a joint power spectrum (JPS) subtraction technique in Fourier plane was proposed, where reference image power spectrum and object image power spectrum are subtracted from the JPS before inverse Fourier-transform operation, it is obvious that the modified JPS removes the zero-order term. Secondly, a fringe-adjusted filter (FAF) was presented to suppress sidelobes and noises. The modified JPS is multiplied by a FAF before the inverse Fourier-transform operation to obtain the cross-correlation peak. Computer simulations demonstrated the improved method can obviously remove zero-order diffraction and effectively suppress the sidelobes and noises compared with classic JTC, and then improve the detection ability for JTC. Experimental results presented the sharp correlation peak and also confirmed the method effectiveness.

Binary joint transform correlator based on differential processing of the joint transform power spectrum

1997 ◽  
Vol 36 (8) ◽  
pp. 1776 ◽  
Author(s):  
Sheng Zhong ◽  
Jiuxing Jiang ◽  
Shutian Liu ◽  
Chunfei Li
Keyword(s):  
Power Spectrum ◽  
Joint Transform Correlator ◽  
Differential Processing

The on-line use of histogram data for high-speed correction and alignment of electron microscope images

1984 ◽  
Vol 42 ◽  
pp. 556-557
Author(s):  
William Krakow
Keyword(s):  
Power Spectrum ◽  
High Speed ◽  
Direct Memory Access ◽  
Digital Television ◽  
Contrast Transfer Function ◽  
The Past ◽  
High Resolution Tem ◽  
On Line ◽  
Correction Of Astigmatism ◽  
The Fourier Transform

In the past few years on-line digital television frame store devices coupled to computers have been employed to attempt to measure the microscope parameters of defocus and astigmatism. The ultimate goal of such tasks is to fully adjust the operating parameters of the microscope and obtain an optimum image for viewing in terms of its information content. The initial approach to this problem, for high resolution TEM imaging, was to obtain the power spectrum from the Fourier transform of an image, find the contrast transfer function oscillation maxima, and subsequently correct the image. This technique requires a fast computer, a direct memory access device and even an array processor to accomplish these tasks on limited size arrays in a few seconds per image. It is not clear that the power spectrum could be used for more than defocus correction since the correction of astigmatism is a formidable problem of pattern recognition.

Log-log scale roughness spectroscopy of surfaces

1993 ◽  
Vol 51 ◽  
pp. 224-225
Author(s):  
P. Fraundorf ◽  
B. Armbruster
Keyword(s):  
Power Spectrum ◽  
Autocorrelation Function ◽  
Power Spectra ◽  
Scanning Force Microscopy ◽  
Scanning Tunneling ◽  
Tunneling Microscopy ◽  
Force Microscopy ◽  
Scanning Force ◽  
Lateral Structure ◽  
Scale Roughness

Optical interferometry, confocal light microscopy, stereopair scanning electron microscopy, scanning tunneling microscopy, and scanning force microscopy, can produce topographic images of surfaces on size scales reaching from centimeters to Angstroms. Second moment (height variance) statistics of surface topography can be very helpful in quantifying “visually suggested” differences from one surface to the next. The two most common methods for displaying this information are the Fourier power spectrum and its direct space transform, the autocorrelation function or interferogram. Unfortunately, for a surface exhibiting lateral structure over several orders of magnitude in size, both the power spectrum and the autocorrelation function will find most of the information they contain pressed into the plot’s origin. This suggests that we plot power in units of LOG(frequency)≡-LOG(period), but rather than add this logarithmic constraint as another element of abstraction to the analysis of power spectra, we further recommend a shift in paradigm.

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