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Polarized image super-resolution via a deep convolutional neural network

OPTICS EXPRESS 2023年第5期31卷 8535-8547页

作者： Hu, Haofeng Yang, Shiyao LI, Xiaobo Cheng, Zhenzhou Liu, Tiegen Zhai, Jingsheng Tianjin Univ Sch Precis Instrument & Optoelect Engn Key Lab Optoelect Informat Technol Minist Educ Tianjin 300072 Peoples R China Tianjin Univ Sch Marine Sci & Technol Tianjin 300072 Peoples R China

Reduced resolution of polarized images makes it difficult to distinguish detailed polarization information and limits the ability to identify small targets and weak signals. A possible way to handle this problem is the polarization super-resolution (SR), which aims to obtain a high-resolution polarized image from a low-resolution one. However, compared with the traditional intensity-mode image SR, the polarization SR is more challenging because more channels and their nonlinear cross-links need to be considered as well as the polarization and intensity information need to be reconstructed simultaneously. This paper analyzes the polarized image degradation and proposes a deep convolutional neural network for polarization SR reconstruction based on two degradation models. The network structure and the well-designed loss function have been verified to effectively balance the restoration of intensity and polarization information, and can realize the SR with a maximum scaling factor of four. Experimental results show that the proposed method outperforms other SR methods in terms of both quantitative evaluation and visual effect evaluation for two degradation models with different scaling factors.(c) 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

关键词： Image metrics Image resolution Imaging systems Neural networks Polarimetric imaging reconstruction algorithms

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Capture the Moment: High-Speed Imaging With Spiking Cameras Through Short-Term Plasticity

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2023年第7期45卷 8127-8142页

作者： Zheng, Yajing Zheng, Lingxiao Yu, Zhaofei Huang, Tiejun Wang, Song Peking Univ Natl Engn Lab Video Technol Sch Comp Sci Beijing 100871 Peoples R China Peking Univ Inst Artificial Intelligence Beijing 100871 Peoples R China Univ South Carolina Dept Comp Sci & Engn Columbia SC 29208 USA

High-speed imaging can help us understand some phenomena that are too fast to be captured by our eyes. Although ultra-fast frame-based cameras (e.g., Phantom) can record millions of fps at reduced resolution, they are too expensive to be widely used. Recently, a retina-inspired vision sensor, spiking camera, has been developed to record external information at 40, 000 Hz. The spiking camera uses the asynchronous binary spike streams to represent visual information. Despite this, how to reconstruct dynamic scenes from asynchronous spikes remains challenging. In this paper, we introduce novel high-speed image reconstruction models based on the short-term plasticity (STP) mechanism of the brain, termed TFSTP and TFMDSTP. We first derive the relationship between states of STP and spike patterns. Then, in TFSTP, by setting up the STP model at each pixel, the scene radiance can be inferred by the states of the models. In TFMDSTP, we use the STP to distinguish the moving and stationary regions, and then use two sets of STP models to reconstruct them respectively. In addition, we present a strategy for correcting error spikes. Experimental results show that the STP-based reconstruction methods can effectively reduce noise with less computing time, and achieve the best performances on both real-world and simulated datasets.

关键词： Cameras Image reconstruction Low latency communication Firing reconstruction algorithms Vision sensors Streaming media High-speed reconstruction motion-dependent short-term plasticity spiking cameras

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Coded aperture compression temporal imaging based on a dual-mask and deep denoiser

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JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION 2023年第7期40卷 1468-1477页

作者： Ge, Youran Qu, Gangrong Huang, Yuhao Liu, Duo Beijing Jiaotong Univ Sch Math & Stat Beijing 100044 Peoples R China

Coded aperture compressive temporal imaging (CACTI) is the mapping of multiple frames using different encoding patterns into a single measurement and then using an algorithm to reconstruct the required high-dimensional signals, thus enabling high-speed photography on low-speed cameras. An encoding pattern and a reconstruction algorithm both play a critical role for CACTI. To improve the quality of the reconstruction, in terms of encoding, we took advantage of the reflective properties of the digital micromirror device and used a complementary dual-mask pattern to obtain more projection information. In terms of decoding, we developed what we believe, to the best of our knowledge, is a new model combining the weighted Landweber regularization with the relaxation strategy and a deep denoiser. The experimental results show the superiority of our proposed encoding-decoding combination, which achieves better performance in terms of the peak SNR, structural similarity index measure, and visual effects. & COPY;2023 Optica Publishing Group

关键词： Compressive imaging Digital micromirror devices High speed photography reconstruction algorithms Spatial light modulators Total internal reflection

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Untrained, physics-informed neural networks for structured illumination microscopy

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OPTICS EXPRESS 2023年第5期31卷 8714-8724页

作者： Burns, Zachary Liu, Zhaowei Univ Calif San Diego Dept Elect & Comp Engn 9500 Gilman Dr La Jolla CA 92093 USA Univ Calif San Diego Mat Sci & Engn Program 9500 Gilman Dr La Jolla CA 92093 USA Univ Calif San Diego Ctr Memory & Recording Res 9500 Gilman Dr La Jolla CA 92093 USA

Structured illumination microscopy (SIM) is a popular super-resolution imaging technique that can achieve resolution improvements of 2x and greater depending on the illumination patterns used. Traditionally, images are reconstructed using the linear SIM reconstruction algorithm. However, this algorithm has hand-tuned parameters which can often lead to artifacts, and it cannot be used with more complex illumination patterns. Recently, deep neural networks have been used for SIM reconstruction, yet they require training sets that are difficult to capture experimentally. We demonstrate that we can combine a deep neural network with the forward model of the structured illumination process to reconstruct sub-diffraction images without training data. The resulting physics-informed neural network (PINN) can be optimized on a single set of diffraction-limited sub-images and thus does not require any training set. We show, with simulated and experimental data, that this PINN can be applied to a wide variety of SIM illumination methods by simply changing the known illumination patterns used in the loss function and can achieve resolution improvements that match theoretical expectations.

关键词： Far field diffraction Image metrics Neural networks reconstruction algorithms Spatial frequency Structured illumination microscopy

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Resolution enhancement via guided filtering for spatial-frequency multiplexing single-shot high-speed imaging

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OPTICS EXPRESS 2023年第21期31卷 34074-34087页

作者： Li, Hang Li, YaHui Sun, BoNan He, Kai Gao, GuiLong Chen, Ping Song, WenYan Wang, Xing Tian, JinShou Chinese Acad Sci Xian Inst Opt & Precis Mech Xian 710119 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Shanxi Univ Collaborat Innovat Ctr Extreme Opt Taiyuan 030006 Peoples R China Northwestern Polytech Univ Sch Power & Energy Xian 710129 Peoples R China

The frequency recognition algorithm for multiple exposures (FRAME) is a progressive single-shot high-speed videography technique that employs the spatial-frequency multiplexing concept to provide high temporal and spatial resolution. However, the inherent crosstalk from the zero-frequency component to the carrier-frequency component leads to resolution degradation and artifacts. To improve recovered frames' quality, we propose a FRAME reconstruction method using guided filters for a removal of the zero-frequency component, which can minimize the artifacts while enhance spatial resolution. A total variation (TV) denoising operation is involved to remove artifacts further to achieve optimized performances. Simulations and experiments were conducted to demonstrate the robust and efficient post-processing capability of the proposed method. With a two-frame experimental system, the results of a USAF 1951 resolution target reveal a 1.8-fold improvement in spatial resolution from 16 lp/mm to 28.5 lp/mm. For complex dynamic scenarios, the wide field of high-speed fuel spray was shot and the proposed method can resolve two droplets with a 30 mu m distance which outperforms the traditional method. (c) 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

关键词： High speed imaging Laser fusion Multiplexing reconstruction algorithms Spatial resolution Temporal resolution

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Deep learning empowered highly compressive SS-OCT via learnable spectral-spatial sub-sampling

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OPTICS LETTERS 2023年第7期48卷 1910-1913页

作者： Ling, Yuye Dong, Zhenxing Li, Xueshen Gan, Yu Su, Yikai Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200240 Peoples R China Stevens Inst Technol Dept Biomed Engn Hoboken NJ USA Shanghai Jiao Tong Univ Dept Elect Engn State Key Lab Adv Opt Commun Syst & Networks Shanghai 200240 Peoples R China

With the rapid advances of light source technology, the A-line imaging rate of swept-source optical coherence tomog-raphy (SS-OCT) has experienced a great increase in the past three decades. The bandwidths of data acquisition, data transfer, and data storage, which can easily reach several hundred megabytes per second, have now been considered major bottlenecks for modern SS-OCT system design. To address these issues, various compression schemes have been previously proposed. However, most of the current meth-ods focus on enhancing the capability of the reconstruction algorithm and can only provide a data compression ratio (DCR) up to 4 without impairing the image quality. In this Letter, we proposed a novel design paradigm, in which the sub-sampling pattern for interferogram acquisition is jointly optimized with the reconstruction algorithm in an end-to -end manner. To validate the idea, we retrospectively apply the proposed method on an ex vivo human coronary opti-cal coherence tomography (OCT) dataset. The proposed method could reach a maximum DCR of-62.5 with peak signal-to-noise ratio (PSNR) of 24.2 dB, while a DCR of-27.78 could yield a visually pleasant image with a PSNR of-24.6 dB. We believe the proposed system could be a viable remedy for the ever-growing data issue in SS-OCT.(c) 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

关键词： Discrete Fourier transforms Image enhancement Image quality Optical coherence tomography reconstruction algorithms Systems design

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Image-free single-pixel object detection

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OPTICS LETTERS 2023年第10期48卷 2527-2530页

作者： Peng, Lintao Xie, Siyu Qin, Tong Cao, Lu Bian, Liheng Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China Beijing Inst Technol Adv Res Inst Multidisciplinary Sci Beijing 100081 Peoples R China Beijing Inst Technol MIIT Key Lab Complex Field Intelligent Sensing Beijing 100081 Peoples R China Natl Innovat Inst Def Technol Beijing 100071 Peoples R China

Recently developed image-free sensing techniques have achieved remarkable performance in various vision tasks. However, existing image-free methods still cannot simultaneously obtain the category, location, and size information of all objects. In this Letter, we report a novel imageenables efficient and robust multi-object detection directly from a small number of measurements, eliminating the requirement for complicated image reconstruction. Different from the conventional full-size pattern sampling method, the reported small-size optimized pattern sampling method achieves higher image-free sensing accuracy with fewer pattern parameters (similar to 1 order of magnitude). Moreover, instead of simply stacking CNN layers, we design the SPOD network based on the transformer architecture. It can better model global features and reinforce the network's attention to the targets in the scene, thus improving the object detection performance. We demonstrate the effectiveness of SPOD on the Voc dataset, which achieves a detection accuracy of 82.41% mAP at a sampling rate of 5% with a refresh rate of 63 f.p.s. (c) 2023 Optica Publishing Group

关键词： Digital micromirror devices Feature extraction Image reconstruction Object detection reconstruction algorithms Vision

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Direct-detected spectroscopy based on a plasmonic Schottky photodetector and a deep neural network

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OPTICS LETTERS 2023年第19期48卷 4965-4968页

作者： Wu, Shaoxiong Chen, Cheng Dai, Yue Ye, Jiayi Xu, Xinyi Liu, Xinyu Tian, Feng Xu, Yang Hu, Huan Zhejiang Univ ZJU UIUC Inst Int Campus Haining 314400 Peoples R China Zhejiang Univ Sch Micronano Elect Hangzhou 310000 Peoples R China Zhejiang Univ State Key Lab Silicon Mat Hangzhou 310000 Peoples R China Zhejiang Univ State Key Lab Fluid Power & Mechatron Syst Hangzhou 310000 Peoples R China

Computational algorithms have facilitated the miniaturization of spectrometers, which is essential for on-chip and portable applications. A plasmonic Schottky photodetector provides a filter-free and CMOS-compatible scheme for spectral measurement. In this study, we report on a direct detected spectral analysis based on an integrated vertically coupled plasmonic nanostructure Schottky photodetector. We demonstrate that the plasmonic Schottky photodetector has a fast response with a -3 dB bandwidth of 600 kHz and a high peak detectivity of 8.65 x 10(10) Jones. By designing a deep neural network (DNN), we demonstrate the reconstruction of the unknown spectrum with a mean square error (MSE) of 1.57 x 10(-4) at a broad operating wave band of 450-950 nm, using only 20 distinct devices. Moreover, the spectral resolution of the 20 devices can reach to 7 nm. These findings provide a promising route for the development of chip-integrated spectrometers with high spectral accuracy and optical performance.

关键词： Light intensity Neural networks Optical components Photodetectors reconstruction algorithms Spectroscopy

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Feature ghost imaging for color identification

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OPTICS EXPRESS 2023年第10期31卷 16213-16226页

作者： Gao, Zihan LI, Minghui Zheng, Peixia Xiong, Jiahao Zhang, Xuan Tang, Zikang Liu, Hong-Chao Univ Macau Inst Appl Phys & Mat Engn Ave Univ Taipa Macau Peoples R China

On the basis of computational ghost imaging (CGI), we present a new imaging tech-nique, feature ghost imaging (FGI), which can convert the color information into distinguishable edge features in retrieved grayscale images. With the edge features extracted by different order operators, FGI can obtain the shape and the color information of objects simultaneously in a single-round detection using one single-pixel detector. The feature distinction of rainbow colors is presented in numerical simulations and the verification of FGI's practical performance is conducted in experiments. Furnishing a new perspective to the imaging of colored objects, our FGI extends the function and the application fields of traditional CGI while sustaining the simplicity of the experimental setup. (c) 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

关键词： Computational imaging Ghost imaging Hyperspectral imaging reconstruction algorithms Spatial light modulators Terahertz spectroscopy

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Rigorous simulation model of double-Ronchi shearing interferometry on lithographic tools

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APPLIED OPTICS 2023年第18期62卷 4759-4765页

作者： Niu, Zhiyuan Li, Sikun Liu, Yang Chinese Acad Sci Shanghai Inst Opt & Fine Mech Shanghai 201800 Peoples R China Dongfang Jingyuan Electron Ltd Beijing 100176 Peoples R China Univ Chinese Acad Sci Beijing 100039 Peoples R China

Double-Ronchi shearing interferometry is widely used in wavefront aberration measurements for advanced lithography projection lens systems. A rigorous simulation model of double-Ronchi shearing interferometry on lithographic tools is the precondition for phase-shifting retrieval algorithm design and error analysis. This paper presents a rigorous simulation model of double-Ronchi shearing interferometry considering the vector nature of light. The model is accurate and can be used in the study of double-Ronchi shearing interferometry. & COPY;2023 Optica Publishing Group

关键词： Light properties Phase shift reconstruction algorithms Shearing interferometry Spatial frequency Wavefront aberrations

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