Advances in two-dimensional spatial frequency modulation imaging (SPIFI) (Conference Presentation)

2020 ◽  
Author(s):  
Alyssa Allende Motz ◽  
Randy A. Bartels ◽  
John Czerski ◽  
Jeffrey J. Field ◽  
Daniel Scarbrough ◽  
...  
Keyword(s):  
Spatial Frequency ◽  
Frequency Modulation ◽  
Two Dimensional

Photographing a Flame by Spatial Frequency Modulation

Nature ◽  
1970 ◽  
Vol 226 (5244) ◽  
pp. 447-448 ◽  
Author(s):  
R. BERNARD ◽  
J. C. GACON
Keyword(s):  
Spatial Frequency ◽  
Frequency Modulation

scholarly journals Contrast and spatial frequency modulation for diagnosis of amblyopia: An electrophysiological approach

2019 ◽  
Vol 31 (1) ◽  
pp. 72-79
Author(s):  
Alireza Mohammadi ◽  
Hassan Hashemi ◽  
Ali Mirzajani ◽  
Abbasali Yekta ◽  
Ebrahim jafarzadehpur ◽  
...  
Keyword(s):  
Spatial Frequency ◽  
Frequency Modulation

Spatial frequency modulation imaging of absorption and fluorescent objects using a single element detector

2011 ◽  
Author(s):  
Gregory Futia ◽  
Philip Schlup ◽  
David G. Winters ◽  
Randy A. Bartels
Keyword(s):  
Spatial Frequency ◽  
Frequency Modulation ◽  
Single Element

Multimodality, multidimensional spatial frequency modulation imaging

2021 ◽  
Author(s):  
Jeffrey A. Squier ◽  
John Czerski ◽  
Daniel Scarbrough ◽  
Dan Adams
Keyword(s):  
Spatial Frequency ◽  
Frequency Modulation

scholarly journals Simultaneous multi-dimensional spatial frequency modulation imaging

2020 ◽  
Vol 14 (1) ◽  
pp. 1-17
Author(s):  
Nathan Worts ◽  
John Czerski ◽  
Jason Jones ◽  
Jeffrey J. Field ◽  
Randy Bartels ◽  
...  
Keyword(s):  
Spatial Frequency ◽  
Frequency Modulation

The Image Watermarking against Shearing Based on Dopplerlet Transformation

2011 ◽  
Vol 181-182 ◽  
pp. 276-280
Author(s):  
Ming Hui Deng ◽  
Wen Zhe Li ◽  
Qi Chen Li
Keyword(s):  
Spatial Frequency ◽  
Dimensional Space ◽  
Image Watermarking ◽  
Time Windows ◽  
Geometric Distortion ◽  
Frequency Change ◽  
Two Dimensional ◽  
Frequency Distributions ◽  
Chirp Signals ◽  
Wigner Transformation

In this paper, a robust image watermarking method in two-dimensional space/spatial-frequency distributions domain is proposed which is robust against geometric distortion. This watermarking is detected by a linear frequency change. The dopplerlet transformation is used to detect the watermark. The chirp signals are used as watermarks and this type of signals is resistant to all stationary filtering methods and exhibits geometrical symmetry. In the two-dimensional Radon-Wigner transformation domain, the chirp signals used as watermarks change only its position in space/spatial-frequency distribution, after applying linear geometrical attack, such as scale rotation and cropping. But the two-dimensional Radon-Wigner transformation needs too much difficult computing. So the image is put into a series of 1D signal by choosing scalable local time windows. The watermark embedded in the dopplerlet transformation domain. The watermark thus generated is invisible and performs well in StirMark test and is robust to geometrical attacks. Compared with other watermarking algorithms, this algorithm is more robust, especially against geometric distortion, while having excellent frequency properties.

scholarly journals Two-Dimensional Spatial Frequency Content and Confusions among Dot Matrix Characters

1979 ◽  
Vol 23 (1) ◽  
pp. 384-388
Author(s):  
Michael E. Maddox
Keyword(s):  
Spatial Frequency ◽  
Similarity Measure ◽  
Similarity Measures ◽  
Final Analysis ◽  
Second Phase ◽  
Two Dimensional ◽  
Two Phase ◽  
Frequency Spectra ◽  
Character Size ◽  
Point Fast Fourier Transform

A two-phase study was conducted which related the confusions among dot matrix characters to the two-dimensional spatial frequency similarity of these characters. During the first phase of the study, subjects were shown single alphanumeric characters from four different dot matrix fonts and five matrix size/character sub-tense combinations. Data from this phase of the research were analyzed in terms of both correctness and character confusion frequencies. The second phase of the study consisted of digitizing and analyzing all characters from two of the fonts used in the first phase. The fonts chosen represent the most and least confusable of the four, based on the performance data obtained. These characters were scanned photometrically using a computer-controlled X-Y stage and subjected to a 512 × 512 point fast Fourier transform (FFT). The Fourier coefficients were correlated for all possible character pairs within each font-matrix/character size cell. These correlations provided an objective similarity measure among characters based upon their 2-D spatial frequency spectra. In addition to the spatial frequency similarity measure, a simple digital Phi coefficient was calculated for each character pair. The final analysis performed in this study was the correlation of observed performance (confusions) with objective similarity measures (2-D spectra and Phi coefficients).

Far‐Field Superresolution Imaging via Spatial Frequency Modulation

2020 ◽  
Vol 14 (11) ◽  
pp. 1900011
Author(s):  
Mingwei Tang ◽  
Xiaowei Liu ◽  
Zhong Wen ◽  
Feihong Lin ◽  
Chao Meng ◽  
...  
Keyword(s):  
Spatial Frequency ◽  
Frequency Modulation ◽  
Far Field ◽  
Superresolution Imaging
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