Fast Edge-Aware Occlusion Detection in the Context of Multispectral Camera Arrays

Sippel F, Seiler J, Kaup A (2024)


Publication Type: Conference contribution, Conference Contribution

Publication year: 2024

Event location: Abu Dhabi AE

URI: https://arxiv.org/abs/2408.14050

Open Access Link: https://arxiv.org/pdf/2408.14050

Abstract

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.

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How to cite

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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