Sippel F, Seiler J, Kaup A (2023)
Publication Language: English
Publication Type: Journal article
Publication year: 2023
Book Volume: 40
Pages Range: 479-491
Journal Issue: 3
URI: https://arxiv.org/abs/2301.07551.pdf
DOI: 10.1364/JOSAA.479552
Open Access Link: https://arxiv.org/abs/2301.07551.pdf
In this paper, a synthetic hyperspectral video database is introduced. Since it is impossible to record ground-truth hyperspectral videos, this database offers the possibility to leverage the evaluation of algorithms in diverse applications. For all scenes, depth maps are provided as well to yield the position of a pixel in all spatial dimensions as well as the reflectance in spectral dimension. Two novel algorithms for two different applications are proposed to prove the diversity of applications that can be addressed by this novel database. First, a cross-spectral image reconstruction algorithm is extended to exploit the temporal correlation between two consecutive frames. The evaluation using this hyperspectral database shows an increase in peak signal-to-noise ratio (PSNR) of up to 5.6 dB dependent on the scene. Second, a hyperspectral video coder is introduced, which extends an existing hyperspectral image coder by exploiting temporal correlation. The evaluation shows rate savings of up to 10% depending on the scene.
APA:
Sippel, F., Seiler, J., & Kaup, A. (2023). Synthetic hyperspectral array video database with applications to cross-spectral reconstruction and hyperspectral video coding. Journal of the Optical Society of America A-Optics Image Science and Vision, 40(3), 479-491. https://dx.doi.org/10.1364/JOSAA.479552
MLA:
Sippel, Frank, Jürgen Seiler, and André Kaup. "Synthetic hyperspectral array video database with applications to cross-spectral reconstruction and hyperspectral video coding." Journal of the Optical Society of America A-Optics Image Science and Vision 40.3 (2023): 479-491.
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