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(a) Schematic of lensfree on-chip imaging using a nanostructured surface is illustrated. (b) SEM image of a structured chip is shown.
(a) Calibration process of a nanostructured transmission surface is outlined. Several far-field calibration images of the patterned chip shown in Fig. 1(b) are also provided. (b) Cross-correlation coefficients of the first calibration frame against all the other calibration images of the same chip are illustrated. (c) Same as part (b), except this time it is measured for a bare glass substrate without the nanopattern. Significantly higher cross-correlation observed in (c) for closely spaced points is the reason for limited spatial resolution of conventional lensfree incoherent imaging without the nanopattern. Nanostructured surfaces break this correlation as shown in (b) to achieve a significantly better resolution.
Experimental proof-of-concept of lensfree on-chip imaging using the nano-structured surface of Fig. 1(b) is demonstrated. Top row shows the lensfree diffraction images of the objects sampled at the CCD for three different incoherent objects. Each diffraction image contains . Bottom row shows the compressive decoding results of these raw diffraction images to resolve subpixel objects on the chip. For comparison, the inset images in the bottom row show regular reflection microscope images of the objects, which very well agree with the reconstruction results. Note that the red colored regions of the inset images refer to the gold coated area with no transmission, and therefore the reconstructions only focus to the dark regions of the chip (at the center of the inset images) that are nanopatterned.
Same as the middle column of Fig. 3, except for different M values. This figure indicates that compressive decoding of a sparse object can be achieved from its diffraction pattern at the far-field even for an under-sampled imaging condition where .
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