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Parallel compressive super-resolution imaging with wide field-of-view based on physics enhanced network
By training the network with the prior OTF of an arbitrary 128x128-pixel region and fine-tuning the network with other OTFs within rest regions of FOV, we realize both mask optimization and super-resolution imaging with up to 1020x1500 wide FOV.
Mid-wave infrared super-resolution imaging based on compressive calibration and sampling
By the use of CS, we measure and calculate the calibration matrix of optical system efficiently and precisely, which improves the imaging contrast and signal-to-noise ratio(SNR) compared with previous work.
Efficient phase retrieval based on dark fringe recognition with an ability of bypassing invalid fringes
This paper discusses the noisy phase retrieval problem: recovering a complex image signal with independent noise from quadratic measurements.
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