Three-dimensional adaptive compression reconstruction method based on liquid crystal hyperspectral calculation imaging system
A computational imaging, compression and reconstruction technology, applied in the field of hyperspectral imaging, can solve problems such as the inability to fully utilize the structural characteristics of the target scene, and achieve the effect of improving three-dimensional super-resolution, reducing difficulty and cost, and saving time.
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Embodiment 1
[0055] like figure 1 As shown, this embodiment discloses a three-dimensional adaptive compression reconstruction method based on a liquid crystal hyperspectral computing imaging system. The liquid crystal hyperspectral computing imaging system includes LCTF with a resolution of N x ×N y coded aperture with a resolution of M x × M y LCTF performs optical filtering on the target scene, and the filtering process is regarded as a compressed sampling process. The matrix after discretization of the LCTF transmittance function is the observation matrix of the spectral dimension. The filtered image contains multiple spectral information, which is spatially modulated through the coded aperture, and finally imaged on the low-resolution detector through the optical lens, and the low-resolution detector collects the compressed observation results after aliasing. The compressed reconstruction method includes the following steps:
[0056] A. Tuning the LCTF so that the coding units of t...
Embodiment 2
[0070] like figure 1 As shown, this embodiment discloses a three-dimensional adaptive compression reconstruction method based on a liquid crystal hyperspectral computing imaging system. The liquid crystal hyperspectral computing imaging system includes LCTF with a resolution of N x ×N y coded aperture with a resolution of M x × M y For the detector and optical lens, see Embodiment 1 for the work of each part. The compressed reconstruction method includes the following steps:
[0071] A. Obtain a low-resolution data cube.
[0072] LCTF can filter the target scene and select the spectral band of a specific central wavelength to pass. In traditional application fields, LCTF is usually considered as an ideal filter with an infinitely small bandwidth, and its output spectral image is a quasi-monochromatic image at the specific central wavelength. In fact, even though the bandwidth of LCTF is very narrow, the image filtered by LCTF is the result of multiplexing of multiple spe...
Embodiment 3
[0101] like figure 2 As shown, this embodiment discloses the simulation results of the above embodiments to demonstrate the superiority of the reconstructed image quality of the present invention.
[0102] In this embodiment, the programming platform used in the simulation experiment is MATLAB R2015b. The original hyperspectral data used in the simulation experiment comes from the hyperspectral database of the Interdisciplinary Computational Vision Laboratory of Ben-Gurion University in Israel. A total of 170 spectral bands from 500nm to 710nm are intercepted, and the spatial dimension of each band is 400×400 pixels. . In the compressed sampling process, LCTF filters the target scene into 22 spectral channels, and the central wavelength of the spectral channels ranges from 500nm to 710nm with an interval of 10nm. The coding aperture compresses and aliases every 8×8 pixels into 1 pixel, that is, the size of the analog detector is 50×50 pixels. In addition, in order to obtai...
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