Single-pixel multispectral imaging based on broadband spectrum multispectral filter arrays

Abstract

Spectral imaging can simultaneously capture the spatial and spectral data of target objects, and provide multidimensional technique for analysis and recognition in many fields, including remote sensing, agriculture and biomedicine. To increase the efficiency of data acquisition, compressed sensing (CS) methods have been introduced into spectral imaging systems, especially single-pixel spectral imaging systems. However, the traditional CS single-pixel spectral imaging system is not stable enough and has complex structure, so we propose a novel macro-pixel segmentation method based on broadband spectrum multispectral filter arrays. In this system, structural illumination and broadband multispectral filter arrays are used to generate spatial modulation and spectral modulation respectively, to modulate 3-D data cube of a scene. The macro-pixel units of the patterns are aimed to capture spatial information, and the sub regions in each macropixel unit are aimed to capture spectral information. The filter arrays can be designed and processed according to specific requirements. By changing the number of sub regions of each macro-pixel unit and the transmittance curve of each sub region, the imaging spectrum can be flexibly changed, and the anti-noise performance of the system can be greatly improved. CS algorithm is used to effectively recover 3-D data cube from one-dimensional signal collected by single-pixel detector. Compared with array detectors (e.g. CCD or CMOS), single-pixel detectors have potential in invisible band and low light applications. Besides, without mechanical or dispersive structure, our strategy has great advantages in miniaturization and integration of spectral imaging equipment.