Fast Capture of Spectral Image Series

In proceedings of 12th International Conference on Computer Graphics Theory and Applications (VISIGRAPP), 2017
 

Abstract

In recent years there has been an increasing interest in multispectral imaging hardware. Among many other applications is the color-correct reproduction of materials. In this paper, we aim at circumventing the limitations of most devices, namely extensive acquisition times for acceptable signal-to-noise-ratios. For this purpose we propose a novel approach to spectral imaging that combines high-quality RGB data and spatial filtering of extremely noisy and sparsely measured spectral information. The capability of handling noisy spectral data allows a dramatic reduction of overall exposure times. The speed-up we achieve allows for spectral imaging at practical acquisition times. We use the RGB images for constraining the reconstruction of dense spectral information from the filtered noisy spectral data. A further important contribution is the extension of a commonly used radiometric calibration method for determining the camera response in the lowest, noise-dominated range of pixel values. We apply our approach both to capturing single high-quality spectral images, as well as to the acquisition of image-based multispectral surface reflectance. Our results demonstrate that we are able to lower the acquisition times for such multispectral reflectance from several days to the few hours necessary for an RGB-based measurement.

Publication

This paper was published at GRAPP 2017: http://dx.doi.org/10.5220/0006175901480159, where it won the Best Student Paper Award.

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Bibtex

@INPROCEEDINGS{2017_merzbach_visigrapp,
     author = {Merzbach, Sebastian and Weinmann, Michael and Rump, Martin and Klein, Reinhard},
      title = {Fast Capture of Spectral Image Series},
  booktitle = {12th International Conference on Computer Graphics Theory and Applications (VISIGRAPP)},
       year = {2017},
   abstract = {In recent years there has been an increasing interest in multispectral imaging hardware. Among many
               other applications is the color-correct reproduction of materials. In this paper, we aim at
               circumventing the limitations of most devices, namely extensive acquisition times for acceptable
               signal-to-noise-ratios. For this purpose we propose a novel approach to spectral imaging that
               combines high-quality RGB data and spatial filtering of extremely noisy and sparsely measured
               spectral information. The capability of handling noisy spectral data allows a dramatic reduction of
               overall exposure times. The speed-up we achieve allows for spectral imaging at practical acquisition
               times. We use the RGB images for constraining the reconstruction of dense spectral information from
               the filtered noisy spectral data. A further important contribution is the extension of a commonly
               used radiometric calibration method for determining the camera response in the lowest,
               noise-dominated range of pixel values. We apply our approach both to capturing single high-quality
               spectral images, as well as to the acquisition of image-based multispectral surface reflectance. Our
               results demonstrate that we are able to lower the acquisition times for such multispectral
               reflectance from several days to the few hours necessary for an RGB-based measurement.}
}