Compressed sensing allows for the reconstruction of images from minimal data by leveraging strong prior knowledge about what those images should look like. The concept of sparsity prior plays a crucial role, favoring models with fewer non-zero parameters. This technique holds potential for applications in astronomy, particularly in enhancing images of the universe from limited observations.
