Point Spread Function

The point spread function (PSF) describes the blurring effect an optical system has on an image, and its accurate modeling and manipulation are crucial for various applications. Current research focuses on improving PSF estimation and engineering techniques, often employing deep learning models like convolutional neural networks, generative adversarial networks, and diffusion models, alongside physics-informed approaches that incorporate optical models into the learning process. These advancements are driving improvements in image deconvolution, super-resolution, depth-from-defocus, and other computational imaging tasks, impacting fields ranging from astronomy and microscopy to computer vision and medical imaging. The development of more accurate and efficient PSF models is essential for enhancing the quality and interpretability of images across diverse scientific disciplines.