Halo performance on low light level image intensifiers

2013 ◽  
Author(s):  
Dongxu Cui ◽  
Ling Ren ◽  
Benkang Chang ◽  
Feng Shi ◽  
Jifang Shi ◽  
...  
Keyword(s):  
Light Level ◽  
Low Light ◽  
Image Intensifiers

Test and analysis of the halo in low-light-level image intensifiers

2012 ◽  
Vol 10 (6) ◽  
pp. 060401-60403 ◽  
Author(s):  
Dongxu Cui Dongxu Cui ◽  
Ling Ren Ling Ren ◽  
Feng Shi Feng Shi ◽  
Jifang Shi Jifang Shi ◽  
Yunsheng Qian Yunsheng Qian ◽  
...  
Keyword(s):  
Light Level ◽  
Low Light ◽  
Image Intensifiers

Effect of pro-proximity pulse voltage on the noise characteristics of generation III low-light-level image intensifiers

Optik ◽  
2018 ◽  
Vol 154 ◽  
pp. 405-410
Author(s):  
Honggang Wang ◽  
Jing Gong ◽  
Gang Wang ◽  
Lili Wang ◽  
Yuzhen Zhang ◽  
...  
Keyword(s):  
Light Level ◽  
Pulse Voltage ◽  
Low Light ◽  
Noise Characteristics ◽  
Image Intensifiers

scholarly journals Denoising and Motion Artifact Removal Using Deformable Kernel Prediction Neural Network for Color-Intensified CMOS

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3891
Author(s):  
Zhenghao Han ◽  
Li Li ◽  
Weiqi Jin ◽  
Xia Wang ◽  
Gangcheng Jiao ◽  
...  
Keyword(s):  
Neural Network ◽  
Noisy Data ◽  
Motion Artifact ◽  
Light Level ◽  
Motion Artifacts ◽  
Night Vision ◽  
Artifact Removal ◽  
Low Light ◽  
Color Imaging ◽  
Image Intensifiers

Image intensifiers are used internationally as advanced military night-vision devices. They have better imaging performance in low-light-level conditions than CMOS/CCD. The intensified CMOS (ICMOS) was developed to satisfy the digital demand of image intensifiers. In order to make the ICMOS capable of color imaging in low-light-level conditions, a liquid-crystal tunable filter based color imaging ICMOS was developed. Due to the time-division color imaging scheme, motion artifacts may be introduced when a moving target is in the scene. To solve this problem, a deformable kernel prediction neural network (DKPNN) is proposed for joint denoising and motion artifact removal, and a data generation method which generates images with color-channel motion artifacts is also proposed to train the DKPNN. The results show that, compared with other denoising methods, the proposed DKPNN performed better both on generated noisy data and on real noisy data. Therefore, the proposed DKPNN is more suitable for color ICMOS denoising and motion artifact removal. A new exploration was made for low-light-level color imaging schemes.

scholarly journals Effect of pro-proximity pulse voltage on the third-generation low light level image intensifiers halo effect

2013 ◽  
Vol 62 (1) ◽  
pp. 014206
Author(s):  
Ren Ling ◽  
Shi Feng ◽  
Guo Hui ◽  
Cui Dong-Xu ◽  
Shi Ji-Fang ◽  
...  
Keyword(s):  
Light Level ◽  
Halo Effect ◽  
Pulse Voltage ◽  
Third Generation ◽  
Low Light ◽  
The Third ◽  
Image Intensifiers

Software pattern recognition applied to nanodiffraction patterns from a STEM instrument

1986 ◽  
Vol 44 ◽  
pp. 694-695
Author(s):  
G.Y. Fan ◽  
J.M. Cowley
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Computer Software ◽  
Processing System ◽  
Light Level ◽  
Host Computer ◽  
Low Light ◽  
Image Processing System ◽  
Recent Developments ◽  
On Line

In recent developments, the ASU HB5 has been modified so that the timing, positioning, and scanning of the finely focused electron probe can be entirely controlled by a host computer. This made the asynchronized handshake possible between the HB5 STEM and the image processing system which consists of host computer (PDP 11/34), DeAnza image processor (IP 5000) which is interfaced with a low-light level TV camera, array processor (AP 400) and various peripheral devices. This greatly facilitates the pattern recognition technique initiated by Monosmith and Cowley. Software called NANHB5 is under development which, instead of employing a set of photo-diodes to detect strong spots on a TV screen, uses various software techniques including on-line fast Fourier transform (FFT) to recognize patterns of greater complexity, taking advantage of the sophistication of our image processing system and the flexibility of computer software.

Low-light-level three-dimensional video microscope with long working distance objective lenses

1994 ◽  
Vol 52 ◽  
pp. 226-227
Author(s):  
W. Lin ◽  
J. Gregorio ◽  
T.J. Holmes ◽  
D. H. Szarowski ◽  
J.N. Turner
Keyword(s):  
Three Dimensional ◽  
Light Level ◽  
Stereo Pair ◽  
Light Illumination ◽  
Initial Image ◽  
Low Light ◽  
Image Recording ◽  
Depth Discrimination ◽  
Video Microscope ◽  
Working Distance

A low-light level video microscope with long working distance objective lenses has been built as part of our integrated three-dimensional (3-D) light microscopy workstation (Fig. 1). It allows the observation of living specimens under sufficiently low light illumination that no significant photobleaching or alternation of specimen physiology is produced. The improved image quality, depth discrimination and 3-D reconstruction provides a versatile intermediate resolution system that replaces the commonly used dissection microscope for initial image recording and positioning of microelectrodes for neurobiology. A 3-D image is displayed on-line to guide the execution of complex experiments. An image composed of 40 optical sections requires 7 minutes to process and display a stereo pair.The low-light level video microscope utilizes long working distance objective lenses from Mitutoyo (10X, 0.28NA, 37 mm working distance; 20X, 0.42NA, 20 mm working distance; 50X, 0.42NA, 20 mm working distance). They provide enough working distance to allow the placement of microelectrodes in the specimen.

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