Abstract: Identification of component damage edges is one of the key factors affecting the resolution of component damage imaging. To improve the imaging precision of the component damage edges, the deep learning-based image optimization of component damage imaging was studied in this paper while using laser ultrasound detection technology. Based on the analysis and processing of ultrasonic Lamb wave in aerospace 4A01 aluminum plate, the amplitude of A0 mode of Lamb wave in the signal was successfully separated. On the basis of amplitude of A0 mode, the visual imaging of the scanned area was completed. An algorithm for optimizing damage edges using convolutional neural network was proposed to carry out the component damage edge optimization experiments. The experimental results show that the algorithm achieves an average improvement of 0.0642 in the structural similarity index measure (SSIM) for each damage type, which significantly improves the imaging precision of damage edge region of components.