Image restoration has been a complex challenge of great interest to researchers, with the main goal of creating visually appealing and natural images while maintaining the perceptual quality of degraded input. In the absence of information about the subject or degraded quality (blind restoration), it is crucial to understand the natural image range. In order to recover facial images, identity information must be included before ensuring that the output retains the individual's unique facial features. Previous research has explored the use of reference-based facial image recovery to address this requirement. However, integrating personalization into blind diffusion-based recovery systems remains an enduring challenge. Adding ...