• Current Optics and Photonics
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• 제7권6호
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• pp.655-664
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• 2023

Ghost imaging (GI) technology is developing rapidly, but there are inevitably some limitations such as the influence of atmospheric turbulence. In this paper, we study a ghost imaging system in atmospheric turbulence and use a gamma-gamma (GG) model to simulate the medium to strong range of turbulence distribution. With a compressed sensing (CS) algorithm and generative adversarial network (GAN), the image can be restored well. We analyze the performance of correlation imaging, the influence of atmospheric turbulence and the restoration algorithm's effects. The restored image's peak signal-to-noise ratio (PSNR) and structural similarity index map (SSIM) increased to 21.9 dB and 0.67 dB, respectively. This proves that deep learning (DL) methods can restore a distorted image well, and it has specific significance for computational imaging in noisy and fuzzy environments.

• 한국광학회:학술대회논문집
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• 한국광학회 2006년도 동계학술발표회 논문집
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• pp.311-312
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• 2006

• 한국광학회:학술대회논문집
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• 한국광학회 2006년도 동계학술발표회 논문집
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• pp.309-310
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• 2006

• Journal of the Optical Society of Korea
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• 제15권4호
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• pp.380-385
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• 2011

Common-path interferometers are widely used for endoscopic optical coherence tomography (OCT) because an arbitrary arm length can be chosen for the endoscopic imaging probe. However, the scheme suffers from the limited range of the sample position distance from the end of the imaging probe because the position between the reference reflector and the sample is limited by the optical path-length difference (OPD) to induce an interference signal. In this study, we developed a novel method for compensating the arbitrary sample position in common-path swept-source OCT by adding an extra Mach-Zehnder interferometer in the post-path of the interfered optical signal. Theoretical analysis and an experimental demonstration of imaging depth tuning for the flexible sample position of an endoscopic OCT image are discussed. After post-tuning of sample position distance, the positioning limitation between the reference reflector and the sample can be solved for various sample positions over a range of 26 mm for the cross-sectional images of a fish eye sample.

• 한국광학회지
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• 제26권5호
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• pp.249-254
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• 2015

본 논문에서는 광 스캐닝 홀로그래피를 이용한 양안식 3차원 홀로그래픽 영상 시스템을 제안하였다. 양안식 3차원 홀로그래픽 영상 시스템을 구현하기 위하여 사람의 두 눈 사이의 거리와 동공의 크기를 고려하여 양안식 3차원 홀로그래픽 디스플레이 시스템을 설계한 뒤 실제 물체의 홀로그램 정보를 획득하였고 수치적인 신호 처리 후 세기 형태의 공간 광 변조기를 이용하여 광학적인 방법으로 복원하였다. 이를 통하여 광 스캐닝 홀로그래피를 이용한 양안식 3차원 홀로그래픽 영상 시스템의 구현 가능성을 실험적으로 확인하였다.

• Current Optics and Photonics
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• 제7권5호
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• pp.545-556
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• 2023

This paper introduces volume-sharing multi-aperture imaging (VMAI), a potential approach proposed for volume reduction in space-borne imagers, with the aim of achieving high-resolution ground spatial imagery using deep learning methods, with reduced volume compared to conventional approaches. As an intermediate step in the VMAI payload development, we present a phase-1 design targeting a 1-meter ground sampling distance (GSD) at 500 km altitude. Although its optical imaging capability does not surpass conventional approaches, it remains attractive for specific applications on small satellite platforms, particularly surveillance missions. The design integrates one wide-field and three narrow-field cameras with volume sharing and no optical interference. Capturing independent images from the four cameras, the payload emulates a large circular aperture to address diffraction and synthesizes high-resolution images using deep learning. Computational simulations validated the VMAI approach, while addressing challenges like lower signal-to-noise (SNR) values resulting from aperture segmentation. Future work will focus on further reducing the volume and refining SNR management.

• Journal of information and communication convergence engineering
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• 제14권1호
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• pp.51-56
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• 2016

In this paper, we present a three-dimensional (3-D) automatic target recognition system based on optical integral imaging reconstruction. In integral imaging, elemental images of the reference and target 3-D objects are obtained through a lenslet array or a camera array. Then, reconstructed 3-D images at various reconstruction depths can be optically generated on the output plane by back-projecting these elemental images onto a display panel. 3-D automatic target recognition can be implemented using computational integral imaging reconstruction and digital nonlinear correlation filters. However, these methods require non-trivial computation time for reconstruction and recognition. Instead, we implement 3-D automatic target recognition using optical cross-correlation between the reconstructed 3-D reference and target images at the same reconstruction depth. Our method depends on an all-optical structure to realize a real-time 3-D automatic target recognition system. In addition, we use a nonlinear correlation filter to improve recognition performance. To prove our proposed method, we carry out the optical experiments and report recognition results.

• 한국통신학회논문지
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• 제34권4C호
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• pp.380-387
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• 2009

본 논문에서는 집적영상(integral imaging) 및 랜덤 픽셀-스크램블링(random pixel-scrambling) 기법을 이용한 새로운 광 영상 암호화(optical image encryption) 방법을 제안하였다. 즉, 제안된 방법의 부호화 과정에서는 먼저 입력영상을 여러 개의 작은 크기의 블록으로 나누어 픽셀-스크램블링을 한 다음 집적 영상 기술을 이용하여 요소영상(elemental image)을 생성하고 이 영상의 안정성을 위하여 2차 픽셀-스크램블링을 수행하여 최종 암호화된 영상을 얻게 된다. 그리고 복호화 과정에서는 암호화된 영상에 광학적인 집적 영상 복원 기법과 역 픽셀-스크램블링 방법을 사용하여 최종적으로 원 영상을 복원하게 된다. 새로이 제안된 광 영상 암호화 기법의 잡음 첨가 및 크로핑과 같은 데이터 손실에 대한 강인성을 실험을 통해 분석하고 그 결과를 제시하였다.

• 센서학회지
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• 제21권3호
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• pp.217-222
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• 2012

Optical coherence tomography(OCT) is a noninvasive optical imaging tool for biomedical applications. OCT can provide depth resolved two/three dimensional morphological images on biological samples. In this paper, we integrated an OCT system that was composed of an SLED(Superluminescent Light Emitting Diode, ${\lambda}_0$=1305 nm bandwith= 141 nm), a reference arm adopting a rapid scanning optical delay line(RSOD) to get high speed imaging, and a sample arm that used a micro electro mechanical systems(MEMS) scanning mirror. The sample arm contained a compact probe for imaging dental structures. The performance of the system was evaluated by imaging in-vivo human teeth with dental calculus, and the results indicated distinct appearance of dental calculus from enamel, gum or decayed teeth. The developed probe and system could successfully confirm the presence of dental calculus with a very high spatial resolution($6{\mu}m$).

• Journal of the Optical Society of Korea
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• 제20권6호
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• pp.752-761
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• 2016

Hyperspectral images are often contaminated with stripe noise, which severely degrades the imaging quality and the precision of the subsequent processing. In this paper, a variational model is proposed by employing spectral-spatial adaptive unidirectional variation and a sparse representation. Unlike traditional methods, we exploit the spectral correction and remove stripes in different bands and different regions adaptively, instead of selecting parameters band by band. The regularization strength adapts to the spectrally varying stripe intensities and the spatially varying texture information. Spectral correlation is exploited via dictionary learning in the sparse representation framework to prevent spectral distortion. Moreover, the minimization problem, which contains two unsmooth and inseparable $l_1$-norm terms, is optimized by the split Bregman approach. Experimental results, on datasets from several imaging systems, demonstrate that the proposed method can remove stripe noise effectively and adaptively, as well as preserve original detail information.