UCLA researchers report a new method for quantitative phase imaging of a 3D phase-only object using a wavelength-multiplexed diffractive optical processor. (IMAGE)
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UCLA researchers report a new method for quantitative phase imaging of a 3D phase-only object using a wavelength-multiplexed diffractive optical processor. Utilizing multiple spatially engineered diffractive layers trained through deep learning, this diffractive processor can optically transform the phase distributions of multiple 2D objects at various axial positions into intensity patterns, each encoded at a unique wavelength channel. These wavelength-multiplexed patterns are projected onto a single field-of-view (FOV) at the output plane of the diffractive processor, enabling the capture of quantitative phase distributions of input objects located at different axial planes using an intensity-only image sensor – eliminating the need for digital phase recovery algorithms.
Credit
C. Shen et al., doi 10.1117/1.AP.6.5.056003.
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