A color fusion method of infrared and low-light-level images based on visual perception

2014 ◽  
Author(s):  
Jing Han ◽  
Minmin Yan ◽  
Yi Zhang ◽  
Lianfa Bai
Keyword(s):  
Visual Perception ◽  
Light Level ◽  
Fusion Method ◽  
Low Light ◽  
Color Fusion

scholarly journals Bionic Algorithm for Color Fusion of Infrared and Low Light Level Image Based on Rattlesnake Bimodal Cells

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 68981-68988 ◽  
Author(s):  
Zhen Zhang ◽  
Huiqi Li ◽  
Guoru Zhao
Keyword(s):  
Light Level ◽  
Low Light ◽  
Color Fusion

Infrared and Low-Light-Level Image Fusion Method Based on Sparse Representation and Color Transfer

2014 ◽  
Vol 511-512 ◽  
pp. 462-466
Author(s):  
Shi Hong Xu ◽  
Guo Qing Huang ◽  
Cun Chao Liu ◽  
Chun Ping Xiong
Keyword(s):  
Image Fusion ◽  
Sparse Representation ◽  
Color Image ◽  
Light Level ◽  
Color Contrast ◽  
Fusion Method ◽  
Color Transfer ◽  
Low Light ◽  
Common Component ◽  
Natural Color

A natural color fusion method for infrared and low-light-level image is proposed. This method utilizes image fusion and color transfer. The fused image uses sparse representation to merge the source images information to be assigned to the Y channel. And then the I and Q channel is combined using Toets method, which extracts the common component from the source images. Finally, the false-color image is obtained by using color transfer technology to the prior pseudo-color YIQ image. Experiments show that the result of our method is information that is more salient, has a higher color contrast, and a more natural color appearance when compared with those produced by the traditional coloration algorithm.

scholarly journals A Dynamic Scene HDR Fusion Method Based on Dual-channel Low-light-level CMOS Camera

2020 ◽  
Vol 42 (4) ◽  
pp. 340-347
Author(s):  
宏 郭 ◽  
理 贺 ◽  
伟其 金 ◽  
果 陈
Keyword(s):  
Light Level ◽  
Fusion Method ◽  
Dynamic Scene ◽  
Cmos Camera ◽  
Low Light ◽  
Dual Channel

Infrared and Low-light-level Visible Light Enhancement Image Fusion Method Based on Latent Low-rank Representation and Composite Filtering

2020 ◽  
Vol 49 (4) ◽  
pp. 410001-410001
Author(s):  
江泽涛 Ze-tao JIANG ◽  
蒋琦 Qi JIANG ◽  
黄永松 Yong-song HUANG ◽  
张少钦 Shao-qin ZHANG
Keyword(s):  
Visible Light ◽  
Image Fusion ◽  
Light Level ◽  
Low Rank ◽  
Fusion Method ◽  
Low Light ◽  
Light Enhancement ◽  
Low Rank Representation ◽  
Image Fusion Method

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.

Color fusion method for night vision based on YUV space

2011 ◽  
Vol 30 (12) ◽  
pp. 3222-3224
Author(s):  
Xiao-yan QIAN ◽  
Lei HAN ◽  
Bang-feng WANG
Keyword(s):  
Night Vision ◽  
Fusion Method ◽  
Color Fusion
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