Sippel F, Seiler J, Kaup A (2024)
Publication Type: Conference contribution, Conference Contribution
Publication year: 2024
URI: https://arxiv.org/abs/2408.14050
Open Access Link: https://arxiv.org/pdf/2408.14050
Multispectral imaging is very beneficial in diverse applications, like
healthcare and agriculture, since it can capture absorption bands of
molecules in different spectral areas. A promising approach for
multispectral snapshot imaging are camera arrays. Image processing is
necessary to warp all different views to the same view to retrieve a
consistent multispectral datacube. This process is also called
multispectral image registration. After a cross spectral disparity
estimation, an occlusion detection is required to find the pixels that
were not recorded by the peripheral cameras. In this paper, a novel fast
edge-aware occlusion detection is presented, which is shown to reduce
the runtime by at least a factor of 12. Moreover, an evaluation on
ground truth data reveals better performance in terms of precision and
recall. Finally, the quality of a final multispectral datacube can be
improved by more than 1.5 dB in terms of PSNR as well as in terms of
SSIM in an existing multispectral registration pipeline. The source code
is available at https://github.com/FAU-LMS/fast-occlusion-detection.
APA:
Sippel, F., Seiler, J., & Kaup, A. (2024). Fast Edge-Aware Occlusion Detection in the Context of Multispectral Camera Arrays. In Proceedings of the 2024 IEEE International Conference on Image Processing. Abu Dhabi, AE.
MLA:
Sippel, Frank, Jürgen Seiler, and André Kaup. "Fast Edge-Aware Occlusion Detection in the Context of Multispectral Camera Arrays." Proceedings of the 2024 IEEE International Conference on Image Processing, Abu Dhabi 2024.
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