Computational microscopy is vital in biomedicine and materials science. Traditional methods struggle with optical aberrations, noise interference, and differences between physical models and real-world imaging, reducing the resolution and accuracy. They rely on pixel-level optimization, which fails to maintain high-quality imaging in complex environments. Therefore, developing a precise and stable computational imaging approach has become a research focus.
