Gerchberg-Saxton algorithm

The Gerchberg-Saxton algorithm is a mathematical technique used for reconstructing images from incomplete or distorted information, often in optics and signal processing. It iteratively enhances an image by alternating between two known constraints: one in the spatial domain (the actual image) and one in the frequency domain (the image's frequency representation). By repeatedly refining the image based on these constraints, the algorithm converges towards a clearer and more accurate final image, making it valuable in applications like holography and optical imaging.