The study of multi-wavelength computational ghost imaging based on feature dimensionality reduction

Hong Wang; Xiaoqian Wang; Chao Gao; Yu Wang; Zhihai Yao

doi:10.1117/12.3016523

30 April 2024 The study of multi-wavelength computational ghost imaging based on feature dimensionality reduction

Hong Wang, Xiaoqian Wang, Chao Gao, Yu Wang, Zhihai Yao

Proceedings Volume 13157, Sixth Conference on Frontiers in Optical Imaging and Technology: Applications of Imaging Technologies; 131570N (2024) https://doi.org/10.1117/12.3016523
Event: Sixth Conference on Frontiers in Optical Imaging Technology and Applications (FOI2023), 2023, Nanjing, JS, China

Abstract

Multi-wavelength computational ghost imaging typically involves extensive data processing and computation, while also facing challenges such as low image reconstruction quality. Various methods have been reported for addressing these issues. In this paper, a method for multi-wavelength computational ghost imaging based on feature dimensionality reduction is proposed. This method enables the reconstruction of high-quality images while maintaining low-complexity computation and storage. The random measurement matrix is initially optimized through singular value decomposition, and the decomposed components are employed as illumination speckles. Following this, the reconstruction of the red, green, or blue component image of the target object is conducted using the second-order correlation function. Next, principal component analysis is applied to perform feature dimensionality reduction on the red, green, and blue component reconstruction images of the object. Simulation results demonstrate that our method can achieve high-quality computational ghost imaging while reducing computational complexity and storage requirements, creating favorable conditions for further optimization of computations.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hong Wang, Xiaoqian Wang, Chao Gao, Yu Wang, and Zhihai Yao "The study of multi-wavelength computational ghost imaging based on feature dimensionality reduction", Proc. SPIE 13157, Sixth Conference on Frontiers in Optical Imaging and Technology: Applications of Imaging Technologies, 131570N (30 April 2024); https://doi.org/10.1117/12.3016523

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