Sparse single-pixel imaging via optimization in nonuniform sampling sparsity

Abstract

Reducing the imaging time while maintaining reconstruction accuracy remains challenging for single-pixel imaging. One cost-effective approach is nonuniform sparse sampling. The existing methods lack intuitive and intrinsic analysis in sparsity. The lack impedes our comprehension of the form’s adjustable range and may potentially limit our ability to identify an optimal distribution form within a confined adjustable range, consequently impacting the method’s overall performance. In this Letter, we report a sparse sampling method with a wide adjustable range and define a sparsity metric to guide the selection of sampling forms. Through a comprehensive analysis and discussion, we select a sampling form that yields satisfying accuracy. These works will make up for the existing methods’ lack of sparsity analysis and help adjust methods to accommodate different situations and needs.