Abstract
Single-pixel imaging (SPI) captures two-dimensional images utilizing a sequence of modulation patterns and measurements recorded by a single-pixel detector. However, the sequential measurement of a scene is time-consuming, especially for high-spatial-resolution imaging. Furthermore, for spectral SPI, the enormous data storage and processing time requirements substantially diminish imaging efficiency. To reduce the required number of patterns, we propose a strategy by optimizing a Hadamard pattern sequence via Morton frequency domain scanning to enhance the quality of a reconstructed spectral cube at low sampling rates. Additionally, we expedite spectral cube reconstruction, eliminating the necessity for a large Hadamard matrix. We demonstrate the effectiveness of our approach through both simulation and experiment, achieving sub-Nyquist sampling of a three-dimensional spectral cube with a spatial resolution of 256 × 256 pixels and 181 spectral bands and a reduction in reconstruction time by four orders of magnitude. Consequently, our method offers an efficient solution for compressed spectral imaging.
Original language | English |
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Article number | 060003 |
Journal | Chinese Optics Letters |
Volume | 22 |
Issue number | 6 |
DOIs | |
Publication status | Published - 10 Jun 2024 |
Keywords
- optimized Hadamard basis
- single-pixel imaging
- spectral imaging