| Summary: | <jats:p>Lensless holography promises compact, low-cost optical apparatus
designs with similar performance to traditional imaging setups. Here,
we propose the use of a silicon micro-LED fabricated in a commercial
CMOS microelectronics process as the illumination source in a lensless
holographic microscope. Its small emission area
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</jats:inline-formula>) ensures high spatial
coherence without the need for a pinhole and results in a large NA
setup, circumventing the limits to the source-to-sample distance
encountered by conventional lensless holography apparatus. The scene
is reconstructed using an untrained deep neural network architecture
that simultaneously performs spectral recovery by learning from the
given single experimental diffraction intensity. We envision this
synergetic combination of CMOS micro-LEDs and the machine learning
framework can be used in other computational imaging applications,
such as a compact microscope for live-cell tracking or spectroscopic
imaging of biological materials.</jats:p>
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