Special Image Pickup Technique for Sensing Invisible. Recent Progress for Infrared Image Sensor Technology.

1997 ◽  
Vol 51 (2) ◽  
pp. 156-161
Author(s):  
Nobukazu Teranishi ◽  
Naoki Oda
Keyword(s):  
Recent Progress ◽  
Infrared Image ◽  
Image Sensor ◽  
Sensor Technology

scholarly journals Mechanical and Electronic Video Stabilization Strategy of Mortars with Trajectory Correction Fuze Based on Infrared Image Sensor

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2461 ◽  
Author(s):  
Cong Zhang ◽  
Dongguang Li
Keyword(s):  
Motion Vector ◽  
Computational Cost ◽  
Infrared Image ◽  
Image Sensor ◽  
Projection Algorithm ◽  
Video Stabilization ◽  
Sensors And Actuators ◽  
Simulation And Experiment ◽  
Transformation Relation ◽  
Trajectory Correction

For a higher attack accuracy of projectiles, a novel mechanical and electronic video stabilization strategy is proposed for trajectory correction fuze. In this design, the complexity of sensors and actuators were reduced. To cope with complex combat environments, an infrared image sensor was used to provide video output. Following the introduction of the fuze’s workflow, the limitation of sensors for mechanical video stabilization on fuze was proposed. Particularly, the parameters of the infrared image sensor that strapdown with fuze were calculated. Then, the transformation relation between the projectile’s motion and the shaky video was investigated so that the electronic video stabilization method could be determined. Correspondingly, a novel method of dividing sub-blocks by adaptive global gray threshold was proposed for the image pre-processing. In addition, the gray projection algorithm was used to estimate the global motion vector by calculating the correlation between the curves of the adjacent frames. An example simulation and experiment were implemented to verify the effectiveness of this strategy. The results illustrated that the proposed algorithm significantly reduced the computational cost without affecting the accuracy of the motion estimation. This research provides theoretical and experimental basis for the intelligent application of sensor systems on fuze.

Infrared image sensor developments supported by the European Space Agency

2019 ◽  
Vol 96 ◽  
pp. 351-360 ◽  
Author(s):  
K. Minoglou ◽  
N. Nelms ◽  
A. Ciapponi ◽  
H. Weber ◽  
S. Wittig ◽  
...  
Keyword(s):  
European Space Agency ◽  
Infrared Image ◽  
Image Sensor ◽  
Space Agency

Design of Imaging Simulation System for Infrared Image Sensor

2013 ◽  
Vol 28 (5) ◽  
pp. 788-792
Author(s):  
程瑶 CHENG Yao ◽  
鲁进 LU Jin ◽  
孟丽娅 MENG Li-ya
Keyword(s):  
Infrared Image ◽  
Image Sensor ◽  
Simulation System ◽  
Imaging Simulation

Deep Image Demosaicing for Submicron Image Sensors

2019 ◽  
Vol 63 (6) ◽  
pp. 60410-1-60410-12
Author(s):  
Irina Kim ◽  
Seongwook Song ◽  
Soonkeun Chang ◽  
Sukhwan Lim ◽  
Kai Guo
Keyword(s):  
Image Quality ◽  
Mobile Devices ◽  
State Of The Art ◽  
Image Sensor ◽  
Sensor Technology ◽  
Color Filter ◽  
Computationally Efficient ◽  
Linear Feature ◽  
Visual Artifacts ◽  
Very High

Abstract Latest trend in image sensor technology allowing submicron pixel size for high-end mobile devices comes at very high image resolutions and with irregularly sampled Quad Bayer color filter array (CFA). Sustaining image quality becomes a challenge for the image signal processor (ISP), namely for demosaicing. Inspired by the success of deep learning approach to standard Bayer demosaicing, we aim to investigate how artifacts-prone Quad Bayer array can benefit from it. We found that deeper networks are capable to improve image quality and reduce artifacts; however, deeper networks can be hardly deployed on mobile devices given very high image resolutions: 24MP, 36MP, 48MP. In this article, we propose an efficient end-to-end solution to bridge this gap—a duplex pyramid network (DPN). Deep hierarchical structure, residual learning, and linear feature map depth growth allow very large receptive field, yielding better details restoration and artifacts reduction, while staying computationally efficient. Experiments show that the proposed network outperforms state of the art for standard and Quad Bayer demosaicing. For the challenging Quad Bayer CFA, the proposed method reduces visual artifacts better than state-of-the-art deep networks including artifacts existing in conventional commercial solutions. While superior in image quality, it is 2‐25 times faster than state-of-the-art deep neural networks and therefore feasible for deployment on mobile devices, paving the way for a new era of on-device deep ISPs.

Advanced image sensor technology for pixel scaling down toward 1.0µm (Invited)

2008 ◽  
Author(s):  
JungChak Ahn ◽  
Chang-Rok Moon ◽  
Bumsuk Kim ◽  
Kyungho Lee ◽  
Yitae Kim ◽  
...  
Keyword(s):  
Image Sensor ◽  
Sensor Technology ◽  
Scaling Down
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