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Image restoration for sparse aperture optical systems

Sparse aperture imaging systems offer high spatial resolution while keeping the total light collection area smaller compared to their fully filled (monolithic) versions. Such systems are of interest in remote sensing and medicine applications where the size, weight, and cost of the imaging system are important. However, these systems often suffer from low image quality resulting from the non-filled sparse aperture structure. In this work, total-variation based image restoration is used to improve the image quality of sparse aperture optical systems. To analyze the performance of image restoration, various periodic subaperture configurations are considered and comparison is also performed with classical Wiener filter. Numerical results demonstrate that sparse aperture imaging systems used with totalvariation based image restoration can achieve similar resolution and image quality as with the equivalent fully filled aperture system.