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Imaging Systems|4 Article(s)
Incoherent Fourier ptychographic photography using structured light
Siyuan Dong, Pariksheet Nanda, Kaikai Guo, Jun Liao, and and Guoan Zheng
Controlling photographic illumination in a structured fashion is a common practice in computational photography and image-based rendering. Here we introduce an incoherent photographic imaging approach, termed Fourier ptychographic photography, that uses nonuniform structured light for super-resolution imaging. In this approach, frequency mixing between the object and the structured light shifts the high-frequency object information to the passband of the photographic lens. Therefore, the recorded intensity images contain object information that is beyond the cutoff frequency of the collection optics. Based on multiple images acquired under different structured light patterns, we used the Fourier ptychographic algorithm to recover the super-resolution object image and the unknown illumination pattern. We demonstrated the reported approach by imaging various objects, including a resolution target, a quick response code, a dollar bill, an insect, and a color leaf. The reported approach may find applications in photographic imaging settings, remote sensing, and imaging radar. It may also provide new insights for high-resolution imaging by shifting the focus from the collection optics to the generation of structured light. Controlling photographic illumination in a structured fashion is a common practice in computational photography and image-based rendering. Here we introduce an incoherent photographic imaging approach, termed Fourier ptychographic photography, that uses nonuniform structured light for super-resolution imaging. In this approach, frequency mixing between the object and the structured light shifts the high-frequency object information to the passband of the photographic lens. Therefore, the recorded intensity images contain object information that is beyond the cutoff frequency of the collection optics. Based on multiple images acquired under different structured light patterns, we used the Fourier ptychographic algorithm to recover the super-resolution object image and the unknown illumination pattern. We demonstrated the reported approach by imaging various objects, including a resolution target, a quick response code, a dollar bill, an insect, and a color leaf. The reported approach may find applications in photographic imaging settings, remote sensing, and imaging radar. It may also provide new insights for high-resolution imaging by shifting the focus from the collection optics to the generation of structured light.
Photonics Research
- Publication Date: Jan. 15, 2015
- Vol. 3, Issue 1, 01000019 (2015)
Nonorthogonal object identification based on ghost imaging
Xiaofan Gu, and Shengmei Zhao
Ghost imaging could be used to make a quick identification of orthogonal objects by means of photocurrent correlation measurements. In this paper, we extend the method to identify nonorthogonal objects. In the method, an object is illuminated by one photon from an entangled pair, and the other one is diffracted into a particular direction by a pre-established multiple-exposure hologram in the idler arm. By the correlation measurements, the nonorthogonal object in the signal arm could be discriminated within a very short time. The constraints for the identification of nonorthogonal objects are presented, which show that the nonorthogonal objects can be discriminated when the overlapping portion between any two objects is less than half of all the objects in the set. The numerical simulations further verify the result. Ghost imaging could be used to make a quick identification of orthogonal objects by means of photocurrent correlation measurements. In this paper, we extend the method to identify nonorthogonal objects. In the method, an object is illuminated by one photon from an entangled pair, and the other one is diffracted into a particular direction by a pre-established multiple-exposure hologram in the idler arm. By the correlation measurements, the nonorthogonal object in the signal arm could be discriminated within a very short time. The constraints for the identification of nonorthogonal objects are presented, which show that the nonorthogonal objects can be discriminated when the overlapping portion between any two objects is less than half of all the objects in the set. The numerical simulations further verify the result.
Photonics Research
- Publication Date: Aug. 24, 2015
- Vol. 3, Issue 5, 05000238 (2015)
Performance analysis of ghost imaging lidar in background light environment
Chenjin Deng, Long Pan, Chenglong Wang, Xin Gao, Wenlin Gong, and Shensheng Han
The effect of background light on the imaging quality of three typical ghost imaging (GI) lidar systems (namely narrow pulsed GI lidar, heterodyne GI lidar, and pulse-compression GI lidar via coherent detection) is investigated. By computing the signal-to-noise ratio (SNR) of fluctuation-correlation GI, our analytical results, which are backed up by numerical simulations, demonstrate that pulse-compression GI lidar via coherent detection has the strongest capacity against background light, whereas the reconstruction quality of narrow pulsed GI lidar is the most vulnerable to background light. The relationship between the peak SNR of the reconstruction image and σ (namely, the signal power to background power ratio) for the three GI lidar systems is also presented, and the results accord with the curve of SNR-σ. The effect of background light on the imaging quality of three typical ghost imaging (GI) lidar systems (namely narrow pulsed GI lidar, heterodyne GI lidar, and pulse-compression GI lidar via coherent detection) is investigated. By computing the signal-to-noise ratio (SNR) of fluctuation-correlation GI, our analytical results, which are backed up by numerical simulations, demonstrate that pulse-compression GI lidar via coherent detection has the strongest capacity against background light, whereas the reconstruction quality of narrow pulsed GI lidar is the most vulnerable to background light. The relationship between the peak SNR of the reconstruction image and σ (namely, the signal power to background power ratio) for the three GI lidar systems is also presented, and the results accord with the curve of SNR-σ.
Photonics Research
- Publication Date: Jul. 10, 2017
- Vol. 5, Issue 5, 05000431 (2017)
Fast reconstructed and high-quality ghost imaging with fast Walsh–Hadamard transform
Le Wang, and Shengmei Zhao
In this paper, we propose a ghost imaging scheme with fast Walsh–Hadamard transform, named GIFWHT. In the scheme, Walsh–Hadamard pattern pairs are used to illuminate an object to generate pairs of detection results, and the corresponding differential detection result is used as the result as that from the conventional bucket detector. By performing the fast Walsh–Hadamard transform on 2k (k is a positive integer) differential detection results, the image of the object can be recovered. The experimental and numerical simulation results show that the reconstruction time of GIFWHT is greatly reduced, and the quality of the recovered image is noticeably improved. In addition, GIFWHT is robust against interference from environmental illumination and could savememory.Network Technology, Ministry of Education (NYKL2015011). In this paper, we propose a ghost imaging scheme with fast Walsh–Hadamard transform, named GIFWHT. In the scheme, Walsh–Hadamard pattern pairs are used to illuminate an object to generate pairs of detection results, and the corresponding differential detection result is used as the result as that from the conventional bucket detector. By performing the fast Walsh–Hadamard transform on 2k (k is a positive integer) differential detection results, the image of the object can be recovered. The experimental and numerical simulation results show that the reconstruction time of GIFWHT is greatly reduced, and the quality of the recovered image is noticeably improved. In addition, GIFWHT is robust against interference from environmental illumination and could savememory.Network Technology, Ministry of Education (NYKL2015011).
Photonics Research
- Publication Date: Nov. 15, 2016
- Vol. 4, Issue 6, 06000240 (2016)
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