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Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

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Hyperspectral photometric stereo for a single capture.

Keisuke Ozawa, Imari Sato, Masahiro Yamaguchi

Journal of the Optical Society of America. A, Optics, Image Science, and Vision

|March 2, 2017

Summary

This study introduces a novel single-capture photometric stereo technique using hyperspectral imaging to accurately estimate surface properties. The method reconstructs 3D surfaces by analyzing spectral and shading information from a single image.

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Area of Science:

Computer Vision
Computational Imaging
Photometry

Background:

Photometric stereo typically requires multiple images under varying illumination.
Hyperspectral imaging captures detailed spectral information, offering potential for enhanced material analysis.

Purpose of the Study:

To develop a single-capture photometric stereo method utilizing a hyperspectral camera.
To enable point-wise estimation of reflectance spectra and surface normals from a single hyperspectral image.

Main Methods:

A spectrally and spatially designed illumination strategy was employed.
Reflectance spectra were measured in wide spectral regions and estimated via interpolation.
Shading information in other spectral regions was utilized for surface normal estimation.

Main Results:

The accuracy of the estimation method was evaluated through simulations.
An experimental setup was created to validate the technique.
Successful surface reconstruction was demonstrated on a real scene.

Conclusions:

The proposed method allows for accurate estimation of reflectance spectra and surface normals from a single hyperspectral image.
This technique offers a promising approach for 3D surface reconstruction in complex scenarios.