When the digital speckle correlation method captures images under certain working conditions, the extreme tilt of the camera leads to a weak correlation between the left and right images, which in turn makes the matching difficult. In order to solve the above problem, a digital speckle stereo matching algorithm based on epipolar correction is proposed in this paper, and an estimation method of deformational iterative initial values of the first-order shape function in the stereo matching process is given through theoretical derivation. The Newton–Raphson (NR) method can be directly used for fine matching in the original left and right images through the estimated deformational iterative initial value. The digital speckle matching experiment under different camera inclination angles of 24.2°, 34.2°, 41.15°, 47.3° and 52.4° was carried out to verify the effectiveness of the digital speckle stereo matching algorithm based on epipolar correction. The experimental results show that this method can complete the matching well under different inclined field of view, and the matching success rate is close to 100%, which can at least meet the requirement of digital speckle matching and deformation strain measurement under the inclination angle less than 52.4° field of view.

数字散斑相关方法在某些工作条件下捕获图像时，相机的极端倾斜会导致左右图像之间的相关性较弱，进而导致匹配困难。为了解决上述问题，本文提出一种基于极线校正的数字散斑立体匹配算法，并通过理论推导给出了立体匹配过程中一阶形函数变形迭代初始值的估计方法。 。通过估计变形迭代初值，可以直接使用牛顿-拉夫森（NR）方法在原始左右图像中进行精细匹配。为了验证基于极线校正的数字散斑立体匹配算法的有效性，进行了24.2°、34.2°、41.15°、47.3°和52.4°不同相机倾角下的数字散斑匹配实验。实验结果表明，该方法能够在不同倾斜视场下很好地完成匹配，匹配成功率接近100%，至少可以满足倾斜角度较小下的数字散斑匹配和形变应变测量的要求。超过 52.4° 的视野。