Satellite ISAR image data intelligent generation method based on diffusion model

The invention relates to a satellite ISAR image data intelligent generation method based on a diffusion model. The method comprises the following steps: utilizing the optical-ISAR image data; training the satellite ISAR image data intelligent generation model by using a preset loss function for carrying out submerged space feature extraction in an optical image domain and a preset loss function for carrying out submerged space feature extraction in an ISAR image domain and using an optimized evidence lower bound as a target function of a reverse diffusion process; a trained satellite ISAR image data intelligent generation model is obtained; and performing image generation on the input satellite image data of the optical domain according to the trained satellite ISAR image data intelligent generation model to obtain a satellite ISAR image. By adopting the method, the conversion between the optical image and the ISAR image can be realized. 本申请涉及一种基于扩散模型的卫星ISAR图像数据智能生成方法。所述方法包括：利用所述光学-ISAR图像数据、预先设置的光学图像域中进行潜空间特征