Single-pixel imaging applies a series of spatial light modulated patterns to subsample the target scene with the assistance of a single-pixel detector, and subsequently reconstructs the object image according to the correlation between patterns and measurements. This indirect image acquisition method ensures reconstruction quality because of the reconstruction algorithm applied, and more crucially, the measurement mask construction. With the introduction of compressed sensing theory, random patterns emerged, but making the measurements blind and lacking specificity. Such patterns fail to facilitate storage and calculation, and thus significantly limit spatial pixel resolution. Recently, Hadamard basis patterns received widespread attention owing to their structured features that enable fast computation and facilitate storage and extraction. Considering this, numerous optimized ordering methods for the Hadamard basis patterns were developed, and proven to significantly reduce the sampling ratios. This study systematically reviews the design frameworks and frontier advances of these methods, and summarizes the future development trends of deterministic pattern construction. Finally, this contribution provides a beneficial reference point including guidance for subsequent research in this specific field.