Optical System for Super Resolution Images

Project goal: To apply compressive sensing theory to the field of optics to create a nominal four times improvement in X and Y image resolution from the detector. High-resolution images are highly sought after in many commercial and military optical systems because they can store large amounts of information, but detector costs increase significantly with pixel count.The Super Resolution Imager SRIdesign incorporates a coded mask, which complicates the point spread function of the optical system. The mask pattern can then be exploited to acquire improved image resolution. To meet the Shannon-Nyquist sampling criterion, the design incorporates a piezoelectric translation stage on the mask to allow multiple image samples to be captured with different mask positions. Representing the samples as a Toeplitz matrix presents them as an undetermined linear system, allowing them to be solved by computer compressive sensing algorithms such as the two-step iterative shrinkage/thresholding, or TwIST, algorithm.