Conventional mid-infrared （MIR） imaging technologies， such as cryogenically cooled infrared focal plane arrays， face significant limitations including high cost， system complexity， high power consumption， and restricted response speed， hindering their application in cost-sensitive and high-frame-rate scenarios. To address these challenges， this study aims to propose and validate a novel， simplified MIR single-pixel imaging （SPI） approach. The core objective is to develop a high-speed， low-cost MIR imaging system that circumvents the need for expensive array detectors by employing a simple rotating coded disk for spatial light modulation， thereby providing a new technical pathway for applications in industrial inspection， biomedicine， and gas sensing.This paper proposes a MIR single-pixel imaging method based on a rotating coded disk for spatial light modulation. The system utilizes a mid-infrared light source to illuminate the target. The transmitted （or reflected） light field is then imaged onto a high-speed rotating coded disk fabricated by patterning a chromium film on a sapphire substrate. This disk dynamically modulates the light field according to a pre-designed cyclic S-matrix pattern. The modulated light is collected by a single-pixel MIR detector， generating a one-dimensional bucket signal sequence. For image reconstruction， a fast Fourier transform （FFT）-based algorithm that exploits the mathematical properties of the cyclic S-matrix is primarily employed to efficiently recover the two-dimensional image from the bucket signal. Furthermore， the performance of various reconstruction algorithms—including Differential Ghost Imaging （DGI）， Quadratic Programming （QP）， Sparse Constraint Reconstruction （SPARSE）， FFT， and Total Variation Minimization （TV）—under different sampling rates is comparatively analyzed through simulations to evaluate image quality and processing speed.Algorithm Comparison （Simulation）： Numerical simulations using a USAF1951 resolution chart target compared five reconstruction algorithms at sampling rates of 100%， 70%， 50%， and 30% （Fig. 3）. Quantitative analysis using Peak Signal-to-Noise Ratio （PSNR） and Structural Similarity Index Measure （SSIM） at 50% sampling rate indicated that a specific iterative algorithm （AP） offered superior reconstruction quality under compressive sampling conditions （Fig. 4）. However， the FFT algorithm demonstrated the shortest reconstruction time at full sampling rate （0.20 seconds）， making it most suitable for real-time imaging requirements （Fig. 5）.Experimental Validation： A proof-of-concept MIR-SPI system was constructed （Fig. 1 schematic）. Using a copper mask of the digit "9" as the target （Fig. 6b）， the system with a 41×43 pixel S-matrix pattern and a disk rotation speed of 8 rps （equivalent to a 14 kHz modulation rate） successfully acquired the bucket signal （Fig. 6a）. The FFT algorithm effectively reconstructed the target image， clearly revealing the digit's structure （Fig. 6c）. Background noise and artifacts present in the initial reconstruction， attributed to mechanical jitter during disk rotation， were significantly suppressed using a noise-optimization algorithm， leading to a cleaner final image （Fig. 6d）. This experiment confirms the feasibility of the proposed rotating-disk-based MIR-SPI scheme.This study successfully designed， simulated， and experimentally demonstrated a mid-infrared single-pixel imaging system based on a rotating coded disk. The system significantly reduces hardware cost and complexity by replacing expensive MIR focal plane arrays with a simple rotating modulator and a single-pixel detector. It achieves imaging at a spatial resolution of 41×43 pixels with a modulation frequency of 14 kHz. Comparative analysis of reconstruction algorithms provides guidance for balancing image quality and processing speed under different sampling conditions. The proposed scheme offers a promising， simplified， and cost-effective alternative for MIR imaging， with potential for broader application in fields such as industrial non-destructive testing and real-time gas monitoring through further optimization of mechanical stability and reconstruction algorithms.