Analysis on the simplified optic coma effect on spectral image inversion of coded aperture spectral imager

Abstract

With the novel spectrum imaging technology development in recent years, the push-broom coded-aperture spectral imaging (PCASI) shows the advantages of high throughput, high SNR, high stability etc. This coded-aperture spectral imaging utilizes fixed-code templates and push-broom mode, which can realize high-precision reconstruction of spatial and spectral information. But during optical lens designing, manufacturing and debugging, there inevitably exist some minor coma errors. Even minor coma errors can reduce image quality. In this paper, we simulate the system optical coma error which influences the quality of reconstructed image, analyze the variantion of the coded aperture in different optical coma effect, and then propose an accurate curve for image quality and optic coma quality in 255× 255 coded template, which provides important references for the design and development of push-broom coded-aperture spectrometer.

Spectral image reconstruction of coded aperture spectral imaging system based on compressed sensing

“…The sampling data of the imaging system are simulated by the computer, where the spatial encodation of the coded template is established by the random 0/1 matrix, the spectral modulation of the dispersed element is established by the ideal linear dispersion model, and the hyperspectral dataset is used as the input [11][12][13]. The obtained simulation images have a resolution of 256 pixels × 256 pixels, a spectral band range of 501nm ~ 718nm, and a total of 32 spectral bands.…”

Calibration and data restoration of light field modulated imaging spectrometer

“…In order to overcome this limitation, snapshot imaging spectrometers [9] have been developed to acquire the datacube simultaneously. There are different designs of snapshot spectrometers, such as, the non-scanning computed-tomography imaging spectrometer (CTIS), [10,11] the image replicating spectrometer (IRIS), [12,13] the image mapping spectrometer (IMS), [14][15][16] the coded aperture snapshot spectral imager (CASSI), [17][18][19][20] multispectral Sagnac interferometry (MSI), [21] and the light field modulated imaging spectrometer (LFMIS). [22][23][24][25] The approaches such as CTIS, CASSI, IRIS, and MSI employ a complex computational strategy to calculate the datacube and have to deal with calibration difficulty, computational complexity, and measurement artifacts.…”