Fourier Transform Infrared Spectrochemical Imaging: Review of Design and Applications with a Focal Plane Array and Multiple Beam Synchrotron Radiation Source

2012 ◽  
Vol 66 (5) ◽  
pp. 475-491 ◽  
Author(s):  
Carol J. Hirschmugl ◽  
Kathleen M. Gough
Keyword(s):  
Synchrotron Radiation ◽  
Focal Plane ◽  
Signal To Noise Ratio ◽  
Focal Plane Array ◽  
Quality Data ◽  
Small Scale ◽  
Signal To Noise ◽  
High Quality ◽  
Mid Infrared ◽  
Noise Ratio

The beamline design, microscope specifications, and initial results from the new mid-infrared beamline (IRENI) are reviewed. Synchrotron-based spectrochemical imaging, as recently implemented at the Synchrotron Radiation Center in Stoughton, Wisconsin, demonstrates the new capability to achieve diffraction limited chemical imaging across the entire mid-infrared region, simultaneously, with high signal-to-noise ratio. IRENI extracts a large swath of radiation (320 hor. × 25 vert. mrads 2 ) to homogeneously illuminate a commercial infrared (IR) microscope equipped with an IR focal plane array (FPA) detector. Wide-field images are collected, in contrast to single-pixel imaging from the confocal geometry with raster scanning, commonly used at most synchrotron beamlines. IRENI rapidly generates high quality, high spatial resolution data. The relevant advantages (spatial oversampling, speed, sensitivity, and signal-to-noise ratio) are discussed in detail and demonstrated with examples from a variety of disciplines, including formalin-fixed and flash-frozen tissue samples, live cells, fixed cells, paint cross-sections, polymer fibers, and novel nanomaterials. The impact of Mie scattering corrections on this high quality data is shown, and first results with a grazing angle objective are presented, along with future enhancements and plans for implementation of similar, small-scale instruments.

Bias voltage optimization for high signal-to-noise ratio microbolometric focal plane array

Optik ◽  
2020 ◽  
Vol 219 ◽  
pp. 165118
Author(s):  
Xiqu Chen ◽  
Hui Zhao ◽  
Chao Fang ◽  
Qiang Lv ◽  
Liangyan Chen
Keyword(s):  
Bias Voltage ◽  
Focal Plane ◽  
Signal To Noise Ratio ◽  
Focal Plane Array ◽  
High Signal ◽  
Signal To Noise ◽  
Noise Ratio

scholarly journals High Signal-to-Noise Ratio Mid-Infrared Quasar Spectral Templates

2013 ◽  
Vol 9 (S304) ◽  
pp. 315-318
Author(s):  
Allison R. Hill ◽  
S. C. Gallagher ◽  
R. P. Deo ◽  
E. Peeters ◽  
Gordon T. Richards
Keyword(s):  
Star Formation ◽  
Signal To Noise Ratio ◽  
Host Galaxy ◽  
High Signal ◽  
Host Galaxies ◽  
Signal To Noise ◽  
Mid Infrared ◽  
High Ionization ◽  
Noise Ratio ◽  
Luminous Objects

AbstractMid-infrared (MIR) quasar spectra exhibit a suite of emission features including high ionization coronal lines from the narrow line region (NLR) illuminated by the ionizing continuum, and hot dust features from grains, as well as polycyclic aromatic hydrocarbons (PAH) features from star formation in the host galaxy. Few features are detected in most spectra because of typically low signal-to-noise ratio (S/N) data. By generating spectral composites in three different luminosity bins from over 180 Spitzer Ifnfrared Spectrograph (IRS) observations, we boost the S/N and reveal important features in the complex spectra. We detect high-ionization, forbidden emission lines in all templates, PAH features in all but the most luminous objects, and broad silicate and graphite features in emission whose strength increases relative to the continuum with luminosity. We find that the intrinsic quasar spectrum for all luminosity templates is consistent, and the differences in the spectra can be explained by host galaxy contamination in the lower luminosity templates. We also posit that star formation may be active in most quasar host galaxies, but the spectral features of star formation are only detectable if the quasar is faint.

Signal to Noise Ratio in Stem and Low-Loss Images

1980 ◽  
Vol 38 ◽  
pp. 236-237
Author(s):  
A. N. Broers
Keyword(s):  
Signal To Noise Ratio ◽  
High Contrast ◽  
Low Loss ◽  
Signal To Noise ◽  
High Quality ◽  
High Brightness ◽  
Electron Sources ◽  
Noise Ratio

The number of pixels or resolution elements in STEM images has frequently been relatively low (< 105) and in many images only a few gray levels can be distinguished. This is surprising considering the high brightness of the electron sources used in most cases, and the high contrast typically present in STEM images. While it is technologically expensive to match the several million resolution elements resolved in high quality TEM images, it is shown here that it is relatively straightforward to produce STEM images containing at least a million resolution elements.

Micro-crack detection method of steel beam surface using stacked autoencoders on massive full-scale sensing strains

2019 ◽  
Vol 19 (4) ◽  
pp. 1175-1187 ◽  
Author(s):  
Qingsong Song ◽  
Yu Chen ◽  
Elias Abdoli Oskoui ◽  
Zheng Fang ◽  
Todd Taylor ◽  
...  
Keyword(s):  
Deep Learning ◽  
Crack Detection ◽  
Detection Method ◽  
Signal To Noise Ratio ◽  
Full Scale ◽  
Signal To Noise ◽  
High Quality ◽  
Strain Measurements ◽  
Feature Representations ◽  
Noise Ratio

Accurate micro-crack detections on the whole surface of civil structures have great significance. Distributed optical fiber sensor based on Brillouin optical time-domain analysis technology exhibits great facility to measure strain distributions along the whole surface of structures with a high spatial resolution, thus providing a potential and competitive solution to the detection problem. However, mainly due to low signal-to-noise ratio in measurements, such sensor system is still limited in crack detection–based structural health monitoring applications. How to extract high-quality micro-crack feature representations from the low signal-to-noise ratio–distributed strain measurements is crucial to solve the problem. It has been demonstrated in field of pattern recognition that deep learning can automatically extract high-quality noise-robust feature representations from mass chaos data. Therefore, a micro-crack detection method is proposed herein based on deep learning to analyze the full-scale strain measurements. Each measurement is normalized and segmented into a set of equal-length subsequences. Autoencoders, a typical kind of building block of deep neural network, are stacked layer-wise into a deep network and then exploited to automatically extract feature representations from the subsequences. Each extracted feature representation is labeled as one of the two categories by a Softmax regression. One category originates in the subsequences acquired from structure sections with crack defects and another from sections without any cracks. The micro-crack detections are achieved by solving such a crack/non-crack binary classification problem. A 15-m-long steel I-beam with artifact crack defects is built up in laboratory to verify the proposed method. Experimental results demonstrate that the minimum size of detectable crack opening width reaches to 23 μm, and besides, the proposed method is significantly better than traditional Fisher linear discriminant analysis method and classical support vector machine on the detection accuracy.

scholarly journals A SOLAR MID-INFRARED TELESCOPE

2019 ◽  
Vol 55 (1) ◽  
pp. 11-16
Author(s):  
J. E. Mendoza-Torres ◽  
J. S. Palacios-Fonseca ◽  
M. Velázquez-de-la-Rosa ◽  
P. Rodríguez-Montero ◽  
A. De-Roa-Campoy ◽  
...  
Keyword(s):  
Control Systems ◽  
Focal Plane ◽  
Angular Resolution ◽  
Signal To Noise Ratio ◽  
Black Body ◽  
Field Of View ◽  
Solar Telescope ◽  
Signal To Noise ◽  
Mid Infrared ◽  
Infrared Telescope

We developed a mid infrared (MIR) solar telescope, centered at 10 µm. Various optical layouts were analyzed based on computer simulations and a RitcheyChretien 6-inches telescope was selected with a plate scale of 2.5′′/mm using a pyroelectric 4 × 16 pixels detector. The angular resolution is 36′′/pixel with a field of view of 9.6′×2.4′. Two germanium filters are used, one at the aperture of thetelescope and another near its focal plane. The detector was characterized with alaboratory black-body. The count values follow a linear relation with the blackbody temperature. The control systems for both the telescope and the detectorwere developed. Proper mechanical supports were designed for the filters, detectorand electronics. The system has been integrated and a user interface was developed. Preliminary observations have been made giving a signal-to-noise ratio of ≈ 1000.

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