scholarly journals Super-resolution imaging of negative-refractive graded-index photonic crystal flat lens

2021 ◽  
Author(s):  
Binming Liang ◽  
Xiao Huang ◽  
Jihong Zheng
Keyword(s):  
Photonic Crystal ◽  
Imaging System ◽  
Super Resolution ◽  
Point Sources ◽  
Image Resolution ◽  
Multiple Point ◽  
Single Image ◽  
Graded Index ◽  
Resolution Imaging ◽  
Flat Lens

Abstract Photonic crystal (PC) not only breaks through the diffraction limit of traditional lenses but also can realize super-resolution imaging. Improving the resolution is the key task of PC imaging. The main work of this paper is to use a graded-index Photonic crystal (GPC) flat lens to improve the image resolution. An air-hole type two-dimensional (2D) GPC structure based on silicon medium is proposed in this paper. Numerical simulations through RSoft reveal that when the medium in the imaging area is air, the full width at half maximum (FWHM) value of a single image reaches 0.362λ. According to the Rayleigh criterion, the images of two point sources 0.57λ apart can also be distinguished. In the imaging system composed of cedar oil and GPC flat lens, the FWHM value of a single image reaches 0.34λ. In addition, the images of multiple point sources 0.49λ apart can still be distinguished.

Multiband super-resolution imaging of graded-index photonic crystal flat lens

2018 ◽  
Vol 51 (20) ◽  
pp. 205103 ◽  
Author(s):  
Jianlan Xie ◽  
Junzhong Wang ◽  
Rui Ge ◽  
Bei Yan ◽  
Exian Liu ◽  
...  
Keyword(s):  
Photonic Crystal ◽  
Super Resolution ◽  
Graded Index ◽  
Resolution Imaging ◽  
Flat Lens

scholarly journals Large object distance and super-resolution graded-index photonic crystal flat lens

2019 ◽  
Vol 27 (7) ◽  
pp. 9601 ◽  
Author(s):  
Shengnan Liang ◽  
Jianlan Xie ◽  
Pinghua Tang ◽  
Jianjun Liu
Keyword(s):  
Photonic Crystal ◽  
Super Resolution ◽  
Large Object ◽  
Graded Index ◽  
Object Distance ◽  
Flat Lens

scholarly journals Remote Sensing Single-Image Resolution Improvement Using A Deep Gradient-Aware Network with Image-Specific Enhancement

2020 ◽  
Vol 12 (5) ◽  
pp. 758 ◽  
Author(s):  
Mengjiao Qin ◽  
Sébastien Mavromatis ◽  
Linshu Hu ◽  
Feng Zhang ◽  
Renyi Liu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Resolution ◽  
Super Resolution ◽  
Image Resolution ◽  
Single Image ◽  
Remote Sensing Images ◽  
Practical Applications ◽  
Specific Enhancement ◽  
Urban Monitoring ◽  
High Resolution Images

Super-resolution (SR) is able to improve the spatial resolution of remote sensing images, which is critical for many practical applications such as fine urban monitoring. In this paper, a new single-image SR method, deep gradient-aware network with image-specific enhancement (DGANet-ISE) was proposed to improve the spatial resolution of remote sensing images. First, DGANet was proposed to model the complex relationship between low- and high-resolution images. A new gradient-aware loss was designed in the training phase to preserve more gradient details in super-resolved remote sensing images. Then, the ISE approach was proposed in the testing phase to further improve the SR performance. By using the specific features of each test image, ISE can further boost the generalization capability and adaptability of our method on inexperienced datasets. Finally, three datasets were used to verify the effectiveness of our method. The results indicate that DGANet-ISE outperforms the other 14 methods in the remote sensing image SR, and the cross-database test results demonstrate that our method exhibits satisfactory generalization performance in adapting to new data.

scholarly journals Quantitative comparison of camera technologies for cost-effective Super-resolution Optical Fluctuation Imaging (SOFI)

2018 ◽  
Author(s):  
Robin Van den Eynde ◽  
Alice Sandmeyer ◽  
Wim Vandenberg ◽  
Sam Duwé ◽  
Wolfgang Hübner ◽  
...  
Keyword(s):  
Live Cell Imaging ◽  
Imaging System ◽  
Fluorescent Proteins ◽  
Imaging Techniques ◽  
Super Resolution ◽  
Cost Effective ◽  
Wide Field ◽  
Cmos Camera ◽  
Resolution Imaging ◽  
Cost Efficient

AbstractSuper-Resolution (SR) fluorescence microscopy is typically carried out on high-end research microscopes. Super-resolution Optical Fluctuation Imaging (SOFI) is a fast SR technique capable of live-cell imaging, that is compatible with many wide-field microscope systems. However, especially when employing fluorescent proteins, a key part of the imaging system is a very sensitive and well calibrated camera sensor. The substantial costs of such systems preclude many research groups from employing super-resolution imaging techniques.Here, we examine to what extent SOFI can be performed using a range of imaging hardware comprising different technologies and costs. In particular, we quantitatively compare the performance of an industry-grade CMOS camera to both state-of-the-art emCCD and sCMOS detectors, with SOFI-specific metrics. We show that SOFI data can be obtained using a cost-efficient industry-grade sensor, both on commercial and home-built microscope systems, though our analysis also readily exposes the merits of the per-pixel corrections performed in scientific cameras.

scholarly journals Super-resolution imaging system based on integrated microsphere objective lens

2020 ◽  
Vol 69 (13) ◽  
pp. 134201
Author(s):  
Yang Song ◽  
Xi-Bin Yang ◽  
Bing Yan ◽  
Chi Wang ◽  
Jian-Mei Sun ◽  
...  
Keyword(s):  
Imaging System ◽  
Super Resolution ◽  
Objective Lens ◽  
Resolution Imaging
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