To solve the problem of weak correlations between speckle images caused by oblique perspectives， a discretized matching method of digital speckle images at large oblique angles is proposed. Based on the rule that the matching of small-sized subsets is relatively little affected by tilt， large-sized seed points are first discretized into small sized seed point clusters. Clusters are then matched， and matching results for small-sized seed point clusters are then integrated to obtain initial values for large-sized seed points. Accurate matching results can be obtained for large-sized seed points after precise adjustments. Oblique images are then completely matched through a seed point diffusion matching strategy. Finally， deformations can be calculated. An image sequence rotated by degrees within a 0–42° span was generated by simulation， and the matching test was carried out over a 7–30 pixel subset radius. Based on the test above， it was determined that oblique angle and subset size are the main factors affecting image matching. Suggestions for selecting key parameters critical for successful matching of oblique images is given. The efficacy of the proposed method is verified， and its comprehensive performance is evaluated. Numerical simulations and experiment results indicate that matching accuracy of the proposed method is within ±0.03 pixel. We also demonstrate that the proposed method effectively improves the rate of success of speckle image correlations in oblique fields of view， which can satisfy the requirements for stable matching of oblique speckle images and deformation measurements below 40°.