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The solar cell is key photovoltaic (PV) device that converts light energy into electricity, and its surface defects are the main reason for the decrease in the efficiency of PV systems. Conventional solar cell defect detection methods are often interfered with by cell substrates and are difficult to detect under high reflection, especially the overlap of substrates and defects. A solar cell defect detection method based on Fourier single-pixel imaging (FSI) is proposed to distinguish periodic substrates and defects in reconstruction by projecting illumination patterns with Fourier fringes, in which the removal of substrates reaches 100%. Meanwhile, for the high reflection present on the solar cell surface, the solar cell is directly treated as a single-pixel detector, which is free from interference from ambient light. The experiment adopts the solar cell itself as an imaging device under highly reflective conditions and removes the interference of the cell substrate by a 4-step phase-shifted FSI reconstruction algorithm to achieve the extraction of four types of defects, each of which is located in a different position of the solar cell substrate, at 10%, 50%, and 100% sampling rates. The method described here complements existing solar cell defect detection approaches and may be applied to enhance photovoltaic testers that rely on real-time correlation measurements, with promising applications in chip inspection and medical cell imaging. • Fourier single-pixel imaging(FSI) method for solar cells defect detection. • By using the solar cell as a photodetector(PD) to avoid the interference of high reflections. • Periodic substrate removal by 4-step phase-shift-based FSI reaches 100% in four different types of defects. [ABSTRACT FROM AUTHOR]