现代电子技术

为保留工业产品图像重要细节，提升整体视觉效果，推动工业产品质量管理智能化水平，文中提出AIGC视域下工业产品图像多尺度细节增强方法。构建AIGC视域下工业产品图像多尺度细节增强模型，依据Retinex理论多尺度分解原始工业产品图像，分为细节层和基础层。通过计算机视觉对多尺度工业产品图像分别进行图像畸变校正、色彩校正，将处理后的工业产品图像输入至生成对抗网络中，依据生成网络与判别网络对抗训练，最终实现工业产品图像多尺度细节增强。通过实验验证，该方法进行畸变图像校正具有高度稳定性，能够适应不同光强环境，最终实现多尺度细节增强结构相似性始终高于95%，能够保留图像原有重要结构特征，凸显工业产品细节信息，有助于工业产品质量管理。

A multi⁃scale detail enhancement method for industrial product images in the perspective of AIGC is proposed to preserve the important details of industrial product images, improve the overall visual effect, and promote the intelligent level of industrial product quality management. The multi ⁃ scale detail enhancement model of the industrial product image in the perspective of AIGC is constructed. The original industrial product image is decomposed into detail layer and base layer according to the Retinex theory. The image distortion correction and color correction of the multi⁃scale industrial product image are carried out by means of computer vision, and the processed industrial product image is input into the generative adversarial network (GAN), and then the multi⁃scale detail enhancement of the processed industrial product image is realized according to the adversarial training of the generative network and the discriminant network. The experimental results show that the proposed method is highly stable in correcting distorted images, and can adapt to different light intensity environments. The structural similarity of multi⁃scale detail enhancement is always higher than 95%. It can be seen that the proposed method can retain the original important structural features of images, and highlight the details of industrial products, so it can contribute to the quality management of industrial products.