Abstract 3D digital image correlation (3D-DIC) is a pivotal non-contact full-field measurement method in experimental mechanics. Traditional 3D-DIC systems rely on multi-camera setups, which face challenges such as high hardware costs, complex synchronization, and limited stereo matching accuracy. Single-camera stereo vision mitigates synchronization issues but introduces inherent resolution loss, compromising measurement accuracy. To address this, we propose LaESR-Diff, a super-resolution diffusion model integrating an optimized enhanced super-resolution generative adversarial network (ESRGAN) with Laplacian noise scheduling. The LaESR-Diff model employs an optimized ESRGAN to generate conditional inputs, enhancing residual-in-residual dense blocks (RRDBs) and incorporating a zero-mean normalized cross-correlation (ZNCC) loss term for speckle image fidelity. A Laplacian noise schedule replaces traditional linear/cosine schedules to preserve high-frequency textures. A dual evaluation system combines general image metrics and 3D-DIC-specific accuracy metrics. Experiments on the “Stereo-DIC Challenge 1.0” dataset show LaESR-Diff achieves PSNR = 26.13 and SSIM = 0.7423 at × 8 scale, reducing surface height and displacement errors by 58.6% and 67.2%, respectively, compared to bicubic interpolation. Laboratory tensile tests confirm LaESR-Diff reduces full-field displacement error in a quadrangular-prism-based virtual stereo system (QVSS) from 4.25% to 1.71%, nearing the basic stereo system (BSS) accuracy. The results demonstrate that the proposed method effectively compensates for the accuracy degradation caused by resolution loss in single-camera systems. This study provides an effective solution for single-camera 3D-DIC accuracy enhancement, with potential applications in other image-based non-contact measurement fields. Data availability The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request. References Strungar, E. M., Yankin, A. S., Zubova, E. M., Babushkin, A. V. & Dushko, A. N. Experimental study of shear properties of 3D woven composite using digital image correlation and acoustic emission. Acta Mech. Sin. 36, 448–459. https://doi.org/10.1007/s10409-019-00921-7 (2020). Luo, H., Yu, L. & Pan, B. Design and