Abstract
The computed tomography image spectrometer (CTIS) is a snapshot hyperspectral imaging technique, which enables hyperspectral image acquisition in a dynamic scene. However, traditional image reconstruction methods with no explicit constraints will introduce high-frequency noise. The low-rank property has been used in hyperspectral image denoising and achieved great effects. We develop an effective method of low-rank estimation (LRE) for CTIS image reconstruction, which shows significant improvements in both the image quality and the spectral quality of the reconstructed image. Compared with the traditional methods, the peak signal-to-noise ratio of the LRE hyperspectral image can be increased by 8 dB, and the spectral-angular mapping can be decreased by 4 times.
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