Intensity-only optical compressive imaging using a multiply scattering material and a double phase retrieval approach

Rajaei, Boshra; Tramei, Eric W.; Gigan, Sylvain; Krząkała, Florent; Daudet, Laurent

doi:10.1109/icassp.2016.7472439

Cited by 22 publications

(19 citation statements)

References 22 publications

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“…A numerical alternative with intensity-only measurements is the double phase retrieval technique [10,11]. Here the TM is directly estimated from measurements obtained by known probe signals at the input.…”

Section: Related Workmentioning

confidence: 99%

Fast Optical System Identification by Numerical Interferometry

Gupta

Gribonval

Daudet³

2020

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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We propose a numerical interferometry method for identification of optical multiply-scattering systems when only intensity can be measured. Our method simplifies the calibration of the optical transmission matrices from a quadratic to a linear inverse problem by first recovering the phase of the measurements. We show that by carefully designing the probing signals, measurement phase retrieval amounts to a distance geometry problem-a multilateration-in the complex plane. Since multilateration can be formulated as a small linear system which is the same for entire rows of the transmission matrix, the phases can be retrieved very efficiently. In order to speed up the subsequent estimation of A, we design calibration signals so as to take advantage of the fast Fourier transform, achieving a complexity almost linear in the number of entries of the transmission matrix. We run experiments on real hardware and use the computed transmission matrix to recover an unseen image behind a scattering medium. Where the previous state-of-the-art method reports hours to find the transmission matrix, our method takes only a few minutes.

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Section: Related Workmentioning

confidence: 99%

Fast Optical System Identification by Numerical Interferometry

Gupta

Gribonval

Daudet³

2020

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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“…These phase retrieval methods have focused on recovering a single source from its Fourier transform magnitude. However, in certain cases, the problem of recovering multiple underlying images from multiple mixed Fourier transform magnitudes of images, called blind multiple input multiple output image phase retrieval (BMIPR), is ever-present in CCD cameras and photosensitive films [19], [20], such as astronomy [11] or light field images [10], [21]. This problem is ill-posed due to the lack of the phase property and the mixing information.…”

Section: Introductionmentioning

confidence: 99%

Blind Multiple-Input Multiple-Output Image Phase Retrieval

Guo

Zhao

et al. 2020

IEEE Trans. Ind. Electron.

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In this paper, we consider the problem of recovering the phase information of the multiple images from the multiple mixed phaseless Short-Time Fourier Transform (STFT) image measurements, which is called the blind multiple input multiple output image phase retrieval (BMIPR) problem. It is an inherently ill-posed problem due to the lack of the phase and mixing information, and the existing phase retrieval algorithms are not explicitly designed for this case. To address the BMIPR phase retrieval problem, an integrated algorithm is presented, which combines a gradient descent (GD) algorithm by minimizing a nonconvex loss function with an independent component analysis (ICA) algorithm and a non-local means (NM) algorithm. Experimental evaluation has been conducted to show that under appropriate conditions the proposed algorithms can explicitly recover the images, the phases of the images and the mixing matrix. In addition, the algorithm is robust to noise. Index Terms-Blind multiple input multiple output image phase retrieval (BMIPR), short-time Fourier transform (STFT), non-convex optimization, independent component analysis (ICA), non-local means (NM).

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“…These phase retrieval methods have focused on recovering a single source from its Fourier transform magnitude. However, in certain cases, the problem of recovering multiple underlying sources from single mixed Fourier transform magnitudes, called multiple input single output (MISO) phase retrieval, is ever-present in CCD cameras and photosensitive films [22,33,40], underwater acoustic signal detection [6,19], and speech enhancement [13,23]. This problem is ill-posed due to a lack of the phase property and the mixing information.…”

Section: Introductionmentioning

confidence: 99%

Multiple Input Single Output Phase Retrieval

Guo

Wang

et al. 2019

Circuits Syst Signal Process

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In this paper, we consider the problem of recovering the phase information of multiple sources from a mixed phaseless Short-Time Fourier Transform (STFT) measurement, which is called multiple input single output (MISO) phase retrieval problem. It is an inherently ill-posed problem due to the lack of the phase and mixing information, and the existing phase retrieval algorithms are not explicitly designed for this case. To address the MISO phase retrieval problem, a least squares (LS) method coupled with an independent component analysis (ICA) algorithm is proposed for the case of sufficiently long window length. When these conditions are not met, an integrated algorithm is

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Intensity-only optical compressive imaging using a multiply scattering material and a double phase retrieval approach

Cited by 22 publications

References 22 publications

Fast Optical System Identification by Numerical Interferometry

Fast Optical System Identification by Numerical Interferometry

Blind Multiple-Input Multiple-Output Image Phase Retrieval

Multiple Input Single Output Phase Retrieval

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