scholarly journals IR Composite Image Generation by Wavelength Band Based on Temperature Synthesis Estimated from IR Target Signature and Background Scene

2019 ◽  
Vol 2019 ◽  
pp. 1-17
Author(s):  
Tae Wuk Bae ◽  
Young Choon Kim ◽  
Sang Ho Ahn

Infrared (IR) target signatures and background scenes are mainly used for military research purposes such as reconnaissance and detection of enemy targets in modern IR imaging systems like IR search and track (IRST) system. For understanding and analyzing IR signatures and backgrounds in the IR imaging systems, an IR wavelength band (WB) conversion which transforms an arbitrary WB image to another WB is very important in the absence of equipment by WB. In addition, IR image synthesis of targets and backgrounds can provide a great deal of information in the IR target detection field. However, the WB conversion is actually a very challenging research due to lack of information on the absorptivity and transmittance of enormous components of an object or atmosphere. In addition, the radiation and reflectance characteristics of short-wave IR (SWIR)-WB are very different from those of long-wave IR (LWIR)-WB and middle-wave IR (MWIR)-WB. Therefore, the WB conversion in this paper is limited only to IR target signatures and monotonous backgrounds, which is commonly used for military purposes, at a long distance. This paper proposes an IR synthesis method for generating a synthesized IR image of three IR-WBs by synthesizing an IR target signature and a real background scene for an arbitrary IR-WB. In the proposed method, each temperature information is first estimated from an IR target signature and IR background image for an arbitrary IR-WB, and then a synthesized temperature image is generated by combining the respective temperature information estimated from the IR target signature and background scene. Finally, the synthesized temperature image is transformed into an IR radiance image of three IR-WBs. Through the proposed method, various IR synthesis experiments are performed for various IR target signature and background scenes.

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2455 ◽  
Author(s):  
Taewuk Bae ◽  
Youngchoon Kim ◽  
Sangho Ahn

Military infrared (IR) imaging systems utilize one or more IR wavelength-bands, among short wavelength IR (SWIR), middle wavelength IR (MWIR), and long wavelength IR (LWIR) band. The IR image wavelength-band conversion which transforms one arbitrary IR wavelength-band image to another IR wavelength-band image is needed for IR signature modeling and image synthesis in the IR systems. However, the IR wavelength-band conversion is very challenging because absorptivity and transmittance of objects and background (atmosphere) are different according to the IR wavelength band and because radiation and reflectance characteristics of the SWIR are very different from the LWIR and MWIR. Therefore, the IR wavelength-band conversion in this paper applies to only IR targets and monotonous backgrounds at a long distance for military purposes. This paper proposes an IR wavelength-band conversion method which transforms one arbitrary IR wavelength-band image to another IR wavelength-band image by using the surface temperature estimation of an object and the error attenuation method for the estimated temperature. The surface temperature of the object is estimated by an approximated Planck’s radiation equation and the error of estimated temperature is corrected by using the slope information of exact radiance along with the approximated one. The corrected surface temperature is used for generating another IR wavelength-band image. The verification of the proposed method is demonstrated through the simulations using actual IR images obtained by thermal equipment.


2014 ◽  
Vol 63 ◽  
pp. 54-61 ◽  
Author(s):  
Young-Choon Kim ◽  
Tae-Wuk Bae ◽  
Hyuk-Ju Kwon ◽  
Byoung-Ik Kim ◽  
Sang-Ho Ahn

Science ◽  
2019 ◽  
Vol 364 (6439) ◽  
pp. eaav9436 ◽  
Author(s):  
Pouya Bashivan ◽  
Kohitij Kar ◽  
James J. DiCarlo

Particular deep artificial neural networks (ANNs) are today’s most accurate models of the primate brain’s ventral visual stream. Using an ANN-driven image synthesis method, we found that luminous power patterns (i.e., images) can be applied to primate retinae to predictably push the spiking activity of targeted V4 neural sites beyond naturally occurring levels. This method, although not yet perfect, achieves unprecedented independent control of the activity state of entire populations of V4 neural sites, even those with overlapping receptive fields. These results show how the knowledge embedded in today’s ANN models might be used to noninvasively set desired internal brain states at neuron-level resolution, and suggest that more accurate ANN models would produce even more accurate control.


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