A compact wide-spectrum imaging spectrometer using freeform surface

2020 ◽  
Vol 459 ◽  
pp. 125097
Author(s):  
Lei Feng ◽  
Yunfeng Nie ◽  
Bin Xiangli ◽  
Lidong Wei ◽  
Xiaoying He ◽  
...  
Keyword(s):  
Wide Spectrum ◽  
Freeform Surface ◽  
Imaging Spectrometer ◽  
Spectrum Imaging

Design of a compact wide-spectrum double-channel prism imaging spectrometer with freeform surface

2018 ◽  
Vol 57 (31) ◽  
pp. 9512 ◽  
Author(s):  
Lei Feng ◽  
Jinsong Zhou ◽  
Lidong Wei ◽  
Xiaoying He ◽  
Yacan Li ◽  
...  
Keyword(s):  
Wide Spectrum ◽  
Freeform Surface ◽  
Imaging Spectrometer ◽  
Double Channel

Compact Dyson imaging spectrometer with large working distance using freeform surface

2019 ◽  
Author(s):  
Lidong Wei ◽  
Lei Feng ◽  
Jinsong Zhou ◽  
Juanjuan Jing ◽  
Yacan Li ◽  
...  
Keyword(s):  
Freeform Surface ◽  
Imaging Spectrometer ◽  
Working Distance

Design of a compact hyperspectral imaging spectrometer with a freeform surface based on anastigmatism

2020 ◽  
Vol 59 (6) ◽  
pp. 1715 ◽  
Author(s):  
Jialun Zhang ◽  
Chao Lin ◽  
Zhenhua Ji ◽  
Hao Wu ◽  
Chengliang Li ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Freeform Surface ◽  
Imaging Spectrometer

Airborne Multispectral Imager Used in the UAV

2014 ◽  
Vol 701-702 ◽  
pp. 283-287
Author(s):  
Chun Yu Wang ◽  
Qing Wei Dong ◽  
Yang Li ◽  
Xin Yue Xie
Keyword(s):  
Imaging System ◽  
Wide Spectrum ◽  
Experimental System ◽  
Digital Signal ◽  
Image Plane ◽  
Image Sensor ◽  
Imaging Spectrometer ◽  
Optical Signals ◽  
Image Acquisition System ◽  
Multispectral Imager

Under existing conditions, the use of optical lens, imaging spectrometer, and the establishment of a rectangular CMOS image sensor spectral imaging system. Wide spectrum of white LED illuminated sample, by ordinary optical imaging lens, then the multi-channel narrowband filter array on the image plane splitting, and finally by the CMOS image acquisition system, converting optical signals into electrical signals, and then converted by the analog-digital converter chip to a digital signal to the computer. Finally, computer-spectral image cube collected for processing. At the same time, the advantages of airborne multispectral imager used in the UAV trials, obtain higher picture quality, and maintain a portable, imaging speed, and further validate the reliability of the experimental system.

Cooling system design for cryogenic imaging spectrometer with wide spectrum and high resolution

2016 ◽  
Vol 45 (3) ◽  
pp. 0323001
Author(s):  
张 月 Zhang Yue ◽  
张 琢 Zhang Zhuo ◽  
苏 云 Su Yun ◽  
郑国宪 Zheng Guoxian
Keyword(s):  
High Resolution ◽  
System Design ◽  
Cooling System ◽  
Wide Spectrum ◽  
Imaging Spectrometer

Mirror based microscope with a super-long working distance in wide spectrum imaging

2013 ◽  
Vol 15 (7) ◽  
pp. 075701 ◽  
Author(s):  
Jian Liu ◽  
Chao Wang ◽  
Weibo Wang ◽  
Jiubin Tan
Keyword(s):  
Wide Spectrum ◽  
Spectrum Imaging ◽  
Working Distance

An example of spectrum imaging used for comparison of EELS quantitative analysis techniques on Al-Li

1991 ◽  
Vol 49 ◽  
pp. 726-727
Author(s):  
John A. Hunt
Keyword(s):  
Quantitative Analysis ◽  
Large Data ◽  
Difference Spectrum ◽  
Large Data Sets ◽  
Foil Thickness ◽  
Data Sets ◽  
Analysis Techniques ◽  
Spectrum Imaging ◽  
Normal Spectrum ◽  
Electron Energy Loss

Spectrum-imaging is a useful technique for comparing different processing methods on very large data sets which are identical for each method. This paper is concerned with comparing methods of electron energy-loss spectroscopy (EELS) quantitative analysis on the Al-Li system. The spectrum-image analyzed here was obtained from an Al-10at%Li foil aged to produce δ' precipitates that can span the foil thickness. Two 1024 channel EELS spectra offset in energy by 1 eV were recorded and stored at each pixel in the 80x80 spectrum-image (25 Mbytes). An energy range of 39-89eV (20 channels/eV) are represented. During processing the spectra are either subtracted to create an artifact corrected difference spectrum, or the energy offset is numerically removed and the spectra are added to create a normal spectrum. The spectrum-images are processed into 2D floating-point images using methods and software described in [1].

Quantitative parallel EELS spectrum imaging developed as a new tool in AEM

1992 ◽  
Vol 50 (2) ◽  
pp. 1202-1203
Author(s):  
Gianluigi Botton ◽  
Gilles L'espérance
Keyword(s):  
Statistical Analysis ◽  
Spatial Resolution ◽  
Personal Computer ◽  
Systematic Study ◽  
Present Author ◽  
Chemical Elements ◽  
Detection Limits ◽  
Research Groups ◽  
Quantitative Performance ◽  
Spectrum Imaging

As interest for parallel EELS spectrum imaging grows in laboratories equipped with commercial spectrometers, different approaches were used in recent years by a few research groups in the development of the technique of spectrum imaging as reported in the literature. Either by controlling, with a personal computer both the microsope and the spectrometer or using more powerful workstations interfaced to conventional multichannel analysers with commercially available programs to control the microscope and the spectrometer, spectrum images can now be obtained. Work on the limits of the technique, in terms of the quantitative performance was reported, however, by the present author where a systematic study of artifacts detection limits, statistical errors as a function of desired spatial resolution and range of chemical elements to be studied in a map was carried out The aim of the present paper is to show an application of quantitative parallel EELS spectrum imaging where statistical analysis is performed at each pixel and interpretation is carried out using criteria established from the statistical analysis and variations in composition are analyzed with the help of information retreived from t/γ maps so that artifacts are avoided.

Energy-filtered imaging of polymer microstructure

1996 ◽  
Vol 54 ◽  
pp. 162-163
Author(s):  
K. Siangchaew ◽  
J. Bentley ◽  
M. Libera
Keyword(s):  
Energy Loss ◽  
Heavy Element ◽  
Spectroscopic Imaging ◽  
Data Set ◽  
Polymer Microstructure ◽  
Entire Energy ◽  
Staining Methods ◽  
Spectrum Imaging ◽  
Resolution Data

Energy-filtered electron-spectroscopic TEM imaging provides a new way to study the microstructure of polymers without heavy-element stains. Since spectroscopic imaging exploits the signal generated directly by the electron-specimen interaction, it can produce richer and higher resolution data than possible with most staining methods. There are basically two ways to collect filtered images (fig. 1). Spectrum imaging uses a focused probe that is digitally rastered across a specimen with an entire energy-loss spectrum collected at each x-y pixel to produce a 3-D data set. Alternatively, filtering schemes such as the Zeiss Omega filter and the Gatan Imaging Filter (GIF) acquire individual 2-D images with electrons of a defined range of energy loss (δE) that typically is 5-20 eV.

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