Imaging beyond aliasing

A sufficiently high spatial sampling is critical for high quality imaging. If the sampling criterion is not met, artifacts appear in the image generally referred to as grating lobes. Probes with a large aperture provide a large field of view, which allows for more efficient inspection. On the other hand this leads to an increase in the number of element to obey the sampling criterion. We have developed a method that reconstructs sparsely sampled data without assuming anything about the medium. The reconstruction method involves an iterative scheme using wave field extrapolation. After the reconstruction an aliasing free dataset is obtained which can be imaged properly. Aliased and non-aliased datasets were modeled based on point diffractors and reflectors with an increasing width. The datasets were imaged using a mapping in the wavenumber-frequency domain. Up to a factor four of under-sampling can be tolerated, providing the same image quality as a properly sampled dataset.