- 标题
- 摘要
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- 实验方案
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Quantitative characterization of super-resolution infrared imaging based on time-varying focal plane coding
摘要： High resolution infrared image has been the goal of an infrared imaging system. In this paper, a super-resolution infrared imaging method using time-varying coded mask is proposed based on focal plane coding and compressed sensing theory. The basic idea of this method is to set a coded mask on the focal plane of the optical system, and the same scene could be sampled many times repeatedly by using time-varying control coding strategy, the super-resolution image is further reconstructed by sparse optimization algorithm. The results of simulation are quantitatively evaluated by introducing the Peak Signal-to-Noise Ratio (PSNR) and Modulation Transfer Function (MTF), which illustrate that the effect of compressed measurement coef?cient r and coded mask resolution m on the reconstructed image quality. Research results show that the proposed method will promote infrared imaging quality effectively, which will be helpful for the practical design of new type of high resolution infrared imaging systems.
关键词： compressed sensing,focal plane coding,modulation transfer function,super-resolution,Infrared imaging system
更新于2025-09-16 10:30:52
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Deep Coupled ISTA Network for Multi-modal Image Super-Resolution
摘要： Given a low-resolution (LR) image, multi-modal image super-resolution (MISR) aims to find the high-resolution (HR) version of this image with the guidance of an HR image from another modality. In this paper, we use a model-based approach to design a new deep network architecture for MISR. We first introduce a novel joint multi-modal dictionary learning (JMDL) algorithm to model cross-modality dependency. In JMDL, we simultaneously learn three dictionaries and two transform matrices to combine the modalities. Then, by unfolding the iterative shrinkage and thresholding algorithm (ISTA), we turn the JMDL model into a deep neural network, called deep coupled ISTA network. Since the network initialization plays an important role in deep network training, we further propose a layer-wise optimization algorithm (LOA) to initialize the parameters of the network before running back-propagation strategy. Specifically, we model the network initialization as a multi-layer dictionary learning problem, and solve it through convex optimization. The proposed LOA is demonstrated to effectively decrease the training loss and increase the reconstruction accuracy. Finally, we compare our method with other state-of-the-art methods in the MISR task. The numerical results show that our method consistently outperforms others both quantitatively and qualitatively at different upscaling factors for various multi-modal scenarios.
关键词： ISTA,multi-modal image super-resolution,dictionary learning,deep neural network
更新于2025-09-16 10:30:52
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Super-resolution interference lithography enabled by non-equilibrium kinetics of photochromic monolayers
摘要： Highly parallelized optical super-resolution lithography techniques are key for realizing bulk volume nanopatterning in materials. The majority of demonstrated STED-inspired lithography schemes are serial writing techniques. Here we use a recently developed model spirothiopyran monolayer photoresist to study the non-equilibrium kinetics of STED-inspired lithography systems to achieve large area interference lithography with super-resolved feature dimensions. The linewidth is predicted to increase with exposure time and the contrast is predicted to go through a maximum, resulting in a narrow window of optimum exposure. Experimental results are found to match with high quantitative accuracy. The low photoinhibition saturation threshold of the spirothiopyran renders it especially conducive for parallelized large area nanopatterning. Lines with 56 and 92 nm FWHM were obtained using serial and parallel patterning, respectively. Functionalization of surfaces with heterobifunctional PEGs enables diverse patterning of any desired chemical functionality on these monolayers. These results provide important insight prior to realizing a highly parallelized volume nanofabrication technique.
关键词： nanopatterning,spirothiopyran,non-equilibrium kinetics,interference lithography,super-resolution lithography
更新于2025-09-12 10:27:22
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Label-Free Super-Resolution Imaging of Transparent Dielectric Objects Assembled on Silver Film by a Microsphere-Assisted Microscope
摘要： In optical microscopy, label-free imaging transparent dielectric objects with sub-wavelength features is still a challenge. We propose a method to super-resolution image a label-free transparent periodic object using the microsphere-assisted bright-field microscope. A two-dimensional array of label-free hexagonally close-packed polystyrene (PS) nanoparticles with a diameter of 250 nm assembled on a silver film coated glass slide can be discerned by coupling a classical optical microscope with a 30-μm-diameter BaTiO3 glass (BTG) microsphere. However, when the PS nanoparticle array with the same diameter is assembled on either a glass slide or a high-reflectance dielectric multilayer coated glass slide, it cannot be resolved. We propose that period plasmonic near-field illumination is generated due to the excitation of surface plasmon polarition modes on periodically structured interfaces. More high-frequency information of the object is coupled into the BTG microsphere lens, resulting in the improvement of imaging resolution.
关键词： transparent dielectric objects,surface plasmon polarition modes,microsphere-assisted microscope,label-free imaging,super-resolution
更新于2025-09-12 10:27:22
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[IEEE 2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS) - Amsterdam, Netherlands (2019.9.24-2019.9.26)] 2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS) - A Pixel Level Scaled Fusion Model to Provide High Spatial-Spectral Resolution for Satellite Images Using LSTM Networks
摘要： Pixel-level fusion of satellite images coming from multiple sensors allows for an improvement in the quality of the acquired data both spatially and spectrally. In particular, multispectral and hyperspectral images have been fused to generate images with a high spatial and spectral resolution. In literature, there are several approaches for this task, nonetheless, those techniques still present a loss of relevant spatial information during the fusion process. This work presents a multi scale deep learning model to fuse multispectral and hyperspectral data, each with high-spatial-and-low-spectral resolution (HSaLS) and low-spatial-and-high-spectral resolution (LSaHS) respectively. As a result of the fusion scheme, a high-spatial-and-spectral resolution image (HSaHS) can be obtained. In order of accomplishing this result, we have developed a new scalable high spatial resolution process in which the model learns how to transition from low spatial resolution to an intermediate spatial resolution level and finally to the high spatial-spectral resolution image. This step-by-step process reduces significantly the loss of spatial information. The results of our approach show better performance in terms of both the structural similarity index and the signal to noise ratio.
关键词： hyperspectral image,Super resolution,Data Fusion,Long Short Term Memory,Pixel level,multispectral image
更新于2025-09-12 10:27:22
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Waveguide-based platform for large-FOV imaging of optically-active defects in 2D materials
摘要： Single-molecule localization microscopy (SMLM) is a powerful tool which is routinely used for nanoscale optical imaging of biological samples. Recently, this approach has been applied to study optically-active defects in two-dimensional (2D) materials. Such defects can not only alter the mechanical and optoelectronic properties of 2D materials, but also bring new functionalities which make them a promising platform for integrated nanophotonics and quantum sensing. Most SMLM approaches, however, provide a field-of-view limited to ~50x50 μm2, which is not sufficient for high-throughput characterization of 2D materials. Moreover, the 2D materials themselves pose an additional challenge as their nanometer-scale thickness prevents efficient far-field excitation of optically-active defects. To overcome these limitations, we present here a waveguide-based platform for large field-of-view imaging of 2D materials via TIRF-like excitation. We use this platform to perform large-scale characterization of point defects in chemical vapor deposition (CVD)-grown hexagonal boron nitride (hBN) on an area of up to 100x1000 μm2 and demonstrate its potential for correlative imaging and high-throughput characterization of defects in 2D materials.
关键词： defects,microscopy,imaging,waveguides,2D materials,super-resolution
更新于2025-09-12 10:27:22
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0.1THz super-resolution imaging based on 3D printed confocal waveguides
摘要： The paper reports a waveguide-based lens-free terahertz (THz) imaging method. It not only inherits the advantages of traditional confocal imaging, but also realizes super-resolution in THz band. The waveguides prepared by a 3D printing and metal-cladding technology can replace the traditional lens to transmit and focus THz wave effectively. For verification, two hollow waveguides (8 mm inner diameter, 60 mm length) were fabricated and a 0.1 THz confocal waveguides imaging system was built. High quality THz images with a minimum resolution of 1.41 mm (less than 1/2 of the wavelength) were obtained by placing the imaging targets at the waveguide’s focus and performing two-dimensional scanning. The focusing mechanism and transmission characteristics of THz in the waveguide are simulated and analyzed. The simulations are in agreement with the experiments.
关键词： terahertz waveguide,3D printed,confocal system,Super-resolution imaging
更新于2025-09-12 10:27:22
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Photoswitchable single-walled carbon nanotubes for super-resolution microscopy in the near-infrared
摘要： The design of single-molecule photoswitchable emitters was the first milestone toward the advent of single-molecule localization microscopy, setting a new paradigm in the field of optical imaging. Several photoswitchable emitters have been developed, but they all fluoresce in the visible or far-red ranges, missing the desirable near-infrared window where biological tissues are most transparent. Moreover, photocontrol of individual emitters in the near-infrared would be highly desirable for elementary optical molecular switches or information storage elements since most communication data transfer protocols are established in this spectral range. Here, we introduce a type of hybrid nanomaterials consisting of single-wall carbon nanotubes covalently functionalized with photoswitching molecules that are used to control the intrinsic luminescence of the single nanotubes in the near-infrared (beyond 1 mm). Through the control of photoswitching, we demonstrate super-localization imaging of nanotubes unresolved by diffraction-limited microscopy.
关键词： single-molecule localization microscopy,near-infrared,super-resolution microscopy,carbon nanotubes,photoswitchable emitters
更新于2025-09-12 10:27:22
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2D resolution improvement via 1D scanning Space-Time Digital Holography (STDH) in Optofluidics
摘要： Space-Time Digital Holography (STDH) exploits the object motion to record the hologram in a hybrid space-time domain. This representation adds new capabilities to conventional DH, such as unlimited extension of the Field of View (FoV) and tunable phase shifting. Here we show that STDH is able to improve the spatial resolution as well. Differently from other super-resolution approaches, stitching between holograms or their spectra is no longer required. Moreover, we introduce a new STDH modality to record and process hybrid space-time representations. This allows improving resolution with one single object scan, paving the way to the use of STDH for superresolution imaging onboard Lab on a Chip devices.
关键词： Space-Time Digital Holography,STDH,Lab on a Chip,optofluidics,super-resolution
更新于2025-09-11 14:15:04
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Synchronized preparation of bi- and tri-qubit entanglement with nitrogen-vacancy centers coupled to microtoroidal resonators
摘要： in natural scene images are often faced with low-Text resolution problem, which brings signi?cant dif?culties to many text-related tasks such as text detection and recognition. In this paper, we propose a novel text-attentional Conditional Generative Adversarial Network (cGAN) model for text image super-resolution (SR). The model enhances the original cGAN by introducing effective channel and spatial attention mechanisms based on the proposed Residual Dense Channel Attention Block and text/non-text segmentation information, which focus the model on the text regions instead of the background of the image to learn more effective representations of text and achieve better text super-resolution result. The proposed model achieves state-of-the-art performances on public text image super-resolution dataset.
关键词： text image,cGAN,segmentation,attention,Super-resolution
更新于2025-09-11 14:15:04