Single-pixel multispectral imaging based on macropixel segmentation method

Abstract

Spectral imaging can capture both spatial and spectral data of a scene, providing an efficient technique for analysis and identification. To improve the efficiency of data acquisition, compressive sensing (CS) methods have been introduced into spectral imaging systems. In this work, we propose a novel macropixel segmentation method to realize effective and non-mechanical single-pixel multispectral imaging. A series of macropixel-based patterns are designed to modulate data cube of target object. Spatial light modulator (SLM) and multispectral filter array are utilized to generate such patterns. CS algorithm is used to recover data cube from 1-D signal acquired by a single-pixel detector. Alignment of binary patterns with the subareas of macropixel filter array is conducted in the experimental set-up. Without mechanical or dispersive structure, the proposed method holds great potential in miniaturization and integration of spectral imaging devices.