Absorption-Based Ranging from Ambient Thermal Radiation without Known Emissivities

Gallastegi, Unay Dorken; Rueda-Chacon, Hoover; Stevens, Martin J.; Goyal, Vivek K

doi:10.1364/cleo_si.2022.sth5j.3

Conference on Lasers and Electro-Optics 2022

DOI: 10.1364/cleo_si.2022.sth5j.3

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Absorption-Based Ranging from Ambient Thermal Radiation without Known Emissivities

Unay Dorken Gallastegi

Hoover Rueda-Chacon

Martin J. Stevens

et al.

Abstract: We present passive absorption-based ranging using long-wave infrared hyperspectral measurements of an outdoor scene. Regularization and parametric modeling of transmittance enable good accuracy without knowing temperatures or emissivities of scene objects, as validated with lidar.

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2024

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References 41 publications

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Affine transform representation for reducing calibration cost on absorption-based LWIR depth sensing

Kushida,

Nakamura,

Matsuda

et al. 2024

Sci Rep

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Multispectral long-wave infrared (LWIR) ranging is a technique that estimates the distance to the object based on wavelength-dependent absorption of LWIR light through the air. Prior works require time-consuming measurements for calibration and solve non-linear inverse problems, which sometimes falls into a local minimum. In this paper, we propose a linear representation that connects the measurements and the scene parameters using the affine matrix. In this representation, the distance and the temperature of the object can be obtained as a closed-form solution and the calibration cost can be reduced to at least three observations. In real-world experiments, we demonstrate that our method is effective to reduce the calibration cost while keeping the precision of the depth estimation.

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Affine transform representation for reducing calibration cost on absorption-based LWIR depth sensing

Kushida,

Nakamura,

Matsuda

et al. 2024

Sci Rep

View full text Add to dashboard Cite

show abstract

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Absorption-Based Ranging from Ambient Thermal Radiation without Known Emissivities

Abstract: We present passive absorption-based ranging using long-wave infrared hyperspectral measurements of an outdoor scene. Regularization and parametric modeling of transmittance enable good accuracy without knowing temperatures or emissivities of scene objects, as validated with lidar.

Cited by 1 publication

References 41 publications

Affine transform representation for reducing calibration cost on absorption-based LWIR depth sensing

Affine transform representation for reducing calibration cost on absorption-based LWIR depth sensing

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