For the stitching of quantum images, the Harris algorithm needs to artificially set the threshold and the local similarity of the image is high, which leads to the high mismatch rate. The quantum image stitching algorithm based on improved Harris and the quadratic normalized cross correlation (NCC) is proposed. In terms of threshold setting, based on the fact that the image repeatability is high, the number of quantum dots or rings of the statistical image sub-region is determined by binarization and threshold reduction to determine the Harris threshold,and as a full-image threshold. In terms of mismatching, the NCC matching is first performed in a small window, and the corner points are initially screened. Then the second NCC is performed on the result with a large window to reduce the mismatch rate. Experimental results show that the proposed algorithm has better accuracy and speed in quantum dot or ring counting. In terms of threshold setting, the proposed algorithm controls the number of corner points within a reasonable range. In the matching stage, the quadratic NCC method reduces the mismatch rate to 4.82%-27.27%. Therefore, the proposed algorithm optimizes the reliability and time overhead of quantum image stitching, and has potential application value in quantum image stitching.