Picosecond Time-resolved Infrared Imaging by a Nonscanning Two-color Infrared Super-resolution Microscope

2007 ◽  
Vol 36 (11) ◽  
pp. 1380-1381 ◽  
Author(s):  
Makoto Sakai ◽  
Tsutomu Ohmori ◽  
Masataka Kinjo ◽  
Nobuhiro Ohta ◽  
Masaaki Fujii
Keyword(s):  
Infrared Imaging ◽  
Super Resolution ◽  
Time Resolved

A real-time atmospheric turbulence mitigation and super-resolution solution for infrared imaging systems

2012 ◽  
Author(s):  
Douglas R. Droege ◽  
Russell C. Hardie ◽  
Brian S. Allen ◽  
Alexander J. Dapore ◽  
Jon C. Blevins
Keyword(s):  
Real Time ◽  
Atmospheric Turbulence ◽  
Infrared Imaging ◽  
Super Resolution ◽  
Imaging Systems

scholarly journals Super-resolution time-resolved imaging using computational sensor fusion

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
C. Callenberg ◽  
A. Lyons ◽  
D. den Brok ◽  
A. Fatima ◽  
A. Turpin ◽  
...  
Keyword(s):  
Sensor Fusion ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Single Photon ◽  
Super Resolution ◽  
Numerical Data ◽  
Data Cube ◽  
Fluorescence Lifetime Imaging ◽  
Time Resolved ◽  
Temporal Precision

AbstractImaging across both the full transverse spatial and temporal dimensions of a scene with high precision in all three coordinates is key to applications ranging from LIDAR to fluorescence lifetime imaging. However, compromises that sacrifice, for example, spatial resolution at the expense of temporal resolution are often required, in particular when the full 3-dimensional data cube is required in short acquisition times. We introduce a sensor fusion approach that combines data having low-spatial resolution but high temporal precision gathered with a single-photon-avalanche-diode (SPAD) array with data that has high spatial but no temporal resolution, such as that acquired with a standard CMOS camera. Our method, based on blurring the image on the SPAD array and computational sensor fusion, reconstructs time-resolved images at significantly higher spatial resolution than the SPAD input, upsampling numerical data by a factor $$12 \times 12$$ 12 × 12 , and demonstrating up to $$4 \times 4$$ 4 × 4 upsampling of experimental data. We demonstrate the technique for both LIDAR applications and FLIM of fluorescent cancer cells. This technique paves the way to high spatial resolution SPAD imaging or, equivalently, FLIM imaging with conventional microscopes at frame rates accelerated by more than an order of magnitude.

Characteristics of infrared imaging systems which benefit from super-resolution reconstruction

2006 ◽  
Author(s):  
Keith Krapels ◽  
Ronald G. Driggers ◽  
Eddie Jacobs ◽  
Stephen Burks ◽  
Susan Young ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Super Resolution ◽  
Imaging Systems

scholarly journals Cooperative Vinculin Binding to Talin Mapped by Time-Resolved Super Resolution Microscopy

Nano Letters ◽  
2016 ◽  
Vol 16 (7) ◽  
pp. 4062-4068 ◽  
Author(s):  
Xian Hu ◽  
Chaoran Jing ◽  
Xiaochun Xu ◽  
Naotaka Nakazawa ◽  
Virginia W. Cornish ◽  
...  
Keyword(s):  
Super Resolution ◽  
Time Resolved ◽  
Super Resolution Microscopy

Error Reduction in Infrared Thermography by Multiframe Super-Resolution

2018 ◽  
Vol 140 (4) ◽  
Author(s):  
Aditya Chandramohan ◽  
Sara K. Lyons ◽  
Justin A. Weibel ◽  
Suresh V. Garimella
Keyword(s):  
Infrared Thermography ◽  
Thermal Stresses ◽  
Infrared Imaging ◽  
Measurement Techniques ◽  
Super Resolution ◽  
Error Reduction ◽  
Temperature Correction ◽  
Dramatic Improvement ◽  
Measuring Surface ◽  
Potential Improvement

Accurate temperature measurement techniques are critical for monitoring hotspots that induce thermal stresses in electronics packages. Infrared thermography is a popular nonintrusive method for emissivity mapping and measuring surface temperature distribution, but is often impeded by the low native resolution of the camera. A promising technique to mitigate these resolution limits is multiframe super-resolution, which uses multiple subpixel shifted images to generate a single high-resolution image. This study quantifies the error reduction offered by multiframe super-resolution to demonstrate the potential improvement for infrared imaging applications. The multiframe super-resolution reconstruction is implemented using an algorithm developed to interpolate the sub-pixel-shifted low-resolution images to a higher resolution grid. Experimental multiframe super-resolution temperature maps of an electronic component are measured to demonstrate the improvement in feature capture and reduction in aliasing effects. Furthermore, emissivity mapping of the component surface is conducted and demonstrates a dramatic improvement in the temperature correction by multiframe super-resolution. A sensitivity analysis is conducted to assess the effect of registration uncertainty on the multiframe super-resolution algorithm; simulated images are used to demonstrate the smoothing effect at sharp emissivity boundaries as well as improvement in the feature size capture based on the native camera resolution. These results show that, within the limitations of the technique, multiframe super-resolution can be an effective approach for improving the accuracy of emissivity-mapped temperature measurements.

Simultaneous digital super-resolution and nonuniformity correction for infrared imaging systems

2015 ◽  
Vol 54 (21) ◽  
pp. 6508 ◽  
Author(s):  
Pablo Meza ◽  
Guillermo Machuca ◽  
Sergio Torres ◽  
Cesar San Martin ◽  
Esteban Vera
Keyword(s):  
Infrared Imaging ◽  
Super Resolution ◽  
Imaging Systems ◽  
Nonuniformity Correction
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