Characteristic analyses of the reflected components of IR signals due to multiple reflection on object surfaces

Dong-Geon Kim; Jun-Hyuk Choi; Tae-Kuk Kim

doi:10.1117/12.897825

26 October 2011 Characteristic analyses of the reflected components of IR signals due to multiple reflection on object surfaces

Dong-Geon Kim, Jun-Hyuk Choi, Tae-Kuk Kim

Author Affiliations +

Proceedings Volume 8180, Image and Signal Processing for Remote Sensing XVII; 818016 (2011) https://doi.org/10.1117/12.897825
Event: SPIE Remote Sensing, 2011, Prague, Czech Republic

Abstract

The major purpose of the present study is to develop a computer code that predicts infrared signals from 3D objects by considering spectral surface properties. In this study, infrared images from the 3D objects are created by calculating the self emitted component and the reflected components by the solar and sky shines. For the reflected components, the BRDF(Bi-Directional Reflectance Distribution Function) which provides a method of describing reflectance as a function of incident and reflected angles and wavelength is used to explain the reflection characteristics of object`s surface. The multiple-reflection effects by using the view factor are included in analyzing the radiative exchange between adjoining meshes where the shadow effect is also included in this calculation. The infrared signals and images obtained by using the software developed in this study and a commercial software (RadThermIR) are compared each other. Results obtained by using the software developed in this study show fairly good agreement with those obtained by the commercial software. Results also show that the reflected radiance is more important in the MWIR images where the reflected radiance is dominant than in the LWIR images where the self emitted radiance is dominant.

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Dong-Geon Kim, Jun-Hyuk Choi, and Tae-Kuk Kim "Characteristic analyses of the reflected components of IR signals due to multiple reflection on object surfaces", Proc. SPIE 8180, Image and Signal Processing for Remote Sensing XVII, 818016 (26 October 2011); https://doi.org/10.1117/12.897825

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