Deep-learning-based CASSI reconstruction with optical aberration correction

Qiuyu Yue; Bingliang Chen; Zhou Xu; Xinyu Liu; Yang Zhang; Zhenrong Zheng

doi:10.1117/12.2686668

27 November 2023 Deep-learning-based CASSI reconstruction with optical aberration correction

Qiuyu Yue, Bingliang Chen, Zhou Xu, Xinyu Liu, Yang Zhang, Zhenrong Zheng

Proceedings Volume 12767, Optoelectronic Imaging and Multimedia Technology X; 1276711 (2023) https://doi.org/10.1117/12.2686668
Event: SPIE/COS Photonics Asia, 2023, Beijing, China

Conference Poster

Abstract

Coded aperture snapshot spectral imaging (CASSI) is a technique that can capture 3D hyperspectral images (HSIs) of scenes in a single shot. However, the quality of the reconstructed HSIs is affected by various optical aberrations and system noise. Existing deep learning methods for HSI reconstruction do not consider these degradation patterns and thus lack generalization ability to real CASSI data. In this paper, we propose a practical method to recover high-quality HSIs from low-quality CASSI data. We use a spectral imaging simulation to generate authentic training data that reflects the optical aberrations of the CASSI system. We then train a generative network on this data to remove blur and chromatic aberrations from the CASSI measurements. Our experiments show that our method can effectively improve the quality of the reconstructed HSIs and can be easily applied to real CASSI systems.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qiuyu Yue, Bingliang Chen, Zhou Xu, Xinyu Liu, Yang Zhang, and Zhenrong Zheng "Deep-learning-based CASSI reconstruction with optical aberration correction", Proc. SPIE 12767, Optoelectronic Imaging and Multimedia Technology X, 1276711 (27 November 2023); https://doi.org/10.1117/12.2686668

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