Improved Spatiotemporal Noise Reduction for Very Low-Light Environments

2016 ◽  
Vol 63 (9) ◽  
pp. 888-892 ◽  
Author(s):  
Won-Jin Lee ◽  
Seong-Won Lee
Keyword(s):  
Noise Reduction ◽  
Low Light ◽  
Spatiotemporal Noise

scholarly journals Adaptive enhancement and noise reduction in very low light-level video

2007 ◽  
Author(s):  
Henrik Malm ◽  
Magnus Oskarsson ◽  
Eric Warrant ◽  
Petrik Clarberg ◽  
Jon Hasselgren ◽  
...  
Keyword(s):  
Noise Reduction ◽  
Light Level ◽  
Low Light ◽  
Adaptive Enhancement

Simultaneous enhancement and noise reduction of a single low-light image

2016 ◽  
Vol 10 (11) ◽  
pp. 840-847 ◽  
Author(s):  
Liang Zhang ◽  
Peiyi Shen ◽  
Xilu Peng ◽  
Guangming Zhu ◽  
Juan Song ◽  
...  
Keyword(s):  
Noise Reduction ◽  
Low Light ◽  
Light Image

Low-light color image enhancement via iterative noise reduction using RGB/NIR sensor

2017 ◽  
Vol 26 (04) ◽  
pp. 1 ◽  
Author(s):  
Hiroki Yamashita ◽  
Daisuke Sugimura ◽  
Takayuki Hamamoto
Keyword(s):  
Noise Reduction ◽  
Image Enhancement ◽  
Color Image ◽  
Low Light ◽  
Color Image Enhancement ◽  
Light Color

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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