The University of Osaka · 물리·천문학
이 교수의 연구실은 머신러닝 기반의 광학 이미징 및 센싱 기술을 핵심으로 하며, 특히 딥러닝을 활용한 비반복적 위상 복원, 파면 센서 설계, 3D 홀로그래피, 산란 매질 내 스펙트럼 분석 등에서 혁신적인 기술을 개발하고 있습니다. 실시간 모니터링과 저비용·단일 촬영 기반의 고성능 이미징을 실현하기 위해 알고리즘과 광학 시스템의 융합을 추구합니다. 특히, 파면 추정, 위상 복원, 산란 매질 내 스펙트럼 복원 등 응용 분야에서의 실용성과 정밀도를 동시에 확보하는 데 초점을 맞추고 있습니다.
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
We present a new class of wavefront sensors by extending their design space based on machine learning. This approach simplifies both the optical hardware and image processing in wavefront sensing. We experimentally demonstrated a variety of image-based wavefront sensing architectures that can directly estimate Zernike coefficients of aberrated wavefronts from a single intensity image by using a convolutional neural network. We also demonstrated that the proposed deep learning wavefront sensor ca
In this paper, we present a noniterative method for 3D computer-generated holography based on deep learning. A convolutional neural network is adapted for directly generating a hologram to reproduce a 3D intensity pattern in a given class. We experimentally demonstrated the proposed method with optical reproductions of multiple layers based on phase-only Fourier holography. Our method is noniterative, but it achieves a reproduction quality comparable with that of iterative methods for a given cl
Abstract In this paper, we analyze a machine-learning-based non-iterative phase retrieval method. Phase retrieval and its applications have been attractive research topics in optics and photonics, for example, in biomedical imaging, astronomical imaging, and so on. Most conventional phase retrieval methods have used iterative processes to recover phase information; however, the calculation speed and convergence with these methods are serious issues in real-time monitoring applications. Machine-l
We present a method for single-shot spectrally resolved imaging through scattering media by using the spectral memory effect of speckles. In our method, a single speckle pattern from a multi-colored object is captured through scattering media with a monochrome image sensor. The color object is recovered by correlation of the captured speckle and a three-dimensional phase retrieval process. The proposed method was experimentally demonstrated by using point sources with different emission spectra
In this Letter, we present wave propagation models of spatially partially coherent (or spatially incoherent) light to compress the computational load of forward and back propagations in inverse problems. In our model, partially coherent light is approximated as a set of random or plane wavefronts passing through spatial bandpass filters, which corresponds to an illumination pupil, and each wave coherently propagates onto a sensor plane through object space. We show that our models reduce the num
In this paper, we present a method for single-shot blind deconvolution incorporating a coded aperture (CA). In this method, we utilize the CA, inserted on the pupil plane, as support constraints in blind deconvolution. Not only an object is estimated, but also a point spread function of turbulence from a single captured image by a reconstruction algorithm with CA support. The proposed method is demonstrated by simulation and an experiment in which point sources are recovered under severe turbule
Optical phase conjugation is a known technique for optically reproducing an object behind a scattering medium. Here we present digital optical phase conjugation through scattering media with spatially and temporally incoherent light. This enables us to eliminate the inevitable light coherence and the need for interferometric measurement for optical phase conjugation. Moreover, we show a method for suppressing background noise, which is critical in incoherent optical phase conjugation. We numeric
We present a method for computer-generated holography (CGH) in which different images are reproduced on both sides of a hologram with a single illumination source. In the proposed method, we use a transmissive spatial light modulator (SLM) and a half mirror (HM) located downstream of the SLM. The light modulated by the SLM is partially reflected by the HM, and the reflected light is modulated again by the SLM for the double-sided image reproduction. We derive an algorithm for double-sided CGH an
Abstract We present a rapid wavefront sensor based on machine learning and using a line-scan camera. The object light wave propagates through a scattering medium. In our method, the scattered light wave undergoes a series of preconditioning steps. The resultant light wave, in which only the wavefront aberration component is emphasized and the reference object light wave is removed, is captured as one-dimensional data using line focusing optics. The captured data are trained by a convolutional ne