To address the issue of degraded image quality caused by interline misalignment in images when line-by-line sampling is performed for imaging in laser-scanning confocal microscopic imaging systems, a dislocation correction method is proposed in this study. Based on prior knowledge that the similarity between natural image lines is high, this study calculates the cross-correlation of even and odd rows of dislocated image to obtain the line misalignment. Additionally, the effect of the image dark regions on the misalignment calculation is eliminated using the k-means clustering algorithm, and the total misalignment is calculated. Under the scanning imaging process, the image is converted into one-dimensional data. Subsequently, a method based on the Fourier transform is used to correct the image data in the frequency domain at the subpixel level. Experiments conducte using the self-constructed laser-scanning confocal imaging system verifies that the proposed algorithm reduces the misalignment by ~96% in a high-speed imaging scene featuring 30 frame/s. Thus, it can effectively correct the dislocation image and offers a certain robustness.