International Conference on Optical Instruments and Technology最新文献_第10页

Squeeze-and-excitation blocks embedded YOLO model for fast target detection under poor imaging conditions 挤压和激励块嵌入YOLO模型，用于在不良成像条件下快速检测目标

International Conference on Optical Instruments and Technology Pub Date : 2022-07-22 DOI: 10.1117/12.2618343

Shuyun Liu, Bo Zhao, Y. Wang, Mengqi Zhu, Huini Fu

引用次数: 1

Enhanced performance integral imaging 3D display method using quarter-overlapped microlens arrays 四分之一重叠微透镜阵列增强性能集成成像三维显示方法

International Conference on Optical Instruments and Technology Pub Date : 2022-07-22 DOI: 10.1117/12.2619521

Nai-Qin Zhao, Juan Liu, Zifeng Zhao

引用次数: 0

A high through-put image colorimeter for ultra-high-resolution micro-led panel inspection 用于超高分辨率微型led面板检测的高通量图像色度计

International Conference on Optical Instruments and Technology Pub Date : 2022-07-22 DOI: 10.1117/12.2614080

Wei Zhou, Jiang He, Xinyu Peng

引用次数: 0

Multi-frame generative network for image super-resolution 图像超分辨率的多帧生成网络

International Conference on Optical Instruments and Technology Pub Date : 2022-07-22 DOI: 10.1117/12.2612129

Q. Zhao, Liquan Dong, Ming Liu, Xuhong Chu, Qingliang Jiao, Bu Ning, Lingqin Kong, Yuejin Zhao, Mei Hui

{"title":"Multi-frame generative network for image super-resolution","authors":"Q. Zhao, Liquan Dong, Ming Liu, Xuhong Chu, Qingliang Jiao, Bu Ning, Lingqin Kong, Yuejin Zhao, Mei Hui","doi":"10.1117/12.2612129","DOIUrl":"https://doi.org/10.1117/12.2612129","url":null,"abstract":"In recent years, the field of image super-resolution has mainly focused on the single-image super-resolution (SISR) task, which is to estimate an HR image from a single LR input. Due to the ill-posed ness of the SISR problem, these methods are limited to increasing the high-frequency details of the image by learning the a priori of the image. And multi-frame super-resolution (MFSR) provides the possibility to reconstruct rich details using the spatial and temporal difference information between images. With the increasing popularity of array camera technology, this key advantage makes MFSR an important issue for practical applications. We propose a new structure to complete the task of multi-frame image super-resolution. Our network takes multiple noisy images as input and generates a denoised, super-resolution RGB image as output. First, we align the multi-frame images by estimating the dense pixel optical flow between the images, and construct an adaptive fusion module to fuse the information of all frames. Then we build a feature fusion network to simultaneously fuse the depth feature information of multiple LR images and the internal features of the initial high-resolution image. In order to evaluate real-world data, We use the BurstSR data set, which includes real images of smartphones and highresolution SLR cameras, to prove the effectiveness of the proposed multiframe image super-resolution algorithm.","PeriodicalId":201899,"journal":{"name":"International Conference on Optical Instruments and Technology","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128237027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

3D face reconstruction based on position map regression network for lesion analysis of port wine stains 基于位置图回归网络的三维人脸重建用于波特酒污渍损伤分析

International Conference on Optical Instruments and Technology Pub Date : 2022-07-22 DOI: 10.1117/12.2613583

Deng Xiao, Ya Zhou, Yingyi Gui, Chenbo Dong, Jiacheng Han

{"title":"3D face reconstruction based on position map regression network for lesion analysis of port wine stains","authors":"Deng Xiao, Ya Zhou, Yingyi Gui, Chenbo Dong, Jiacheng Han","doi":"10.1117/12.2613583","DOIUrl":"https://doi.org/10.1117/12.2613583","url":null,"abstract":"The evaluation of port wine stain based on three-dimensional information can overcome the inaccuracy of twodimensional image evaluation methods commonly used in clinic. In this paper, an end-to-end multitasking method is designed for the application of 3D information acquisition of port wine stain. Based on deep learning and position map regression network, the reconstruction from 2D pictures to face 3D point cloud is realized. the facial information of patients with port wine stain is represented by UV position map recording 3D point information of the face, and the dense relationship between 3D points and points with semantic meaning in UV space is characterized with this method. The deep learning network framework based on Encoder-Decoder structure is used to complete unconstrained end-to-end face alignment and 3D face reconstruction, whose parameters are obtained by training the data set with lightweight CNN structure. In the process of neural network training and end-to-end unconstrained image facial reconstruction, each point on the UV position map can be assigned different weights, which can not only be used to improve the network performance in neural network training, but also be used to assign corresponding weights to the focus areas with different disease course in the three-dimensional information reconstruction of the focus area therefore the accuracy of the reconstruction results can be increased. With the help of this method, the three-dimensional reconstruction results can be quickly obtained from a single patient's face image, which can be used for subsequent accurate lesion information analysis and treatment.","PeriodicalId":201899,"journal":{"name":"International Conference on Optical Instruments and Technology","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130913672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A multi-depth augmented reality head-up display system using holographic optical elements 采用全息光学元件的多深度增强现实平视显示系统

International Conference on Optical Instruments and Technology Pub Date : 2022-07-22 DOI: 10.1117/12.2619460

Zhenlv Lv, Juan Liu, Liangfa Xu

引用次数: 0

High speed structured illumination microscopy based on compressed sensing: numerical simulation 基于压缩感知的高速结构照明显微镜:数值模拟

International Conference on Optical Instruments and Technology Pub Date : 2022-07-22 DOI: 10.1117/12.2619610

Jiaqi Zeng, Zhang Chonglei, Shao Zongshuo, Xiaocong Yuan

{"title":"High speed structured illumination microscopy based on compressed sensing: numerical simulation","authors":"Jiaqi Zeng, Zhang Chonglei, Shao Zongshuo, Xiaocong Yuan","doi":"10.1117/12.2619610","DOIUrl":"https://doi.org/10.1117/12.2619610","url":null,"abstract":"In traditional optical microscopy imaging system, the resolution of time mainly depends on the detector’s detection speed, usually in millisecond or microsecond magnitude. While the spatial resolution is limited by the optical diffraction limit, the lateral resolution of ordinary microscopies generally only reaches 200nm.Just as biological structure has a wide spatial scale, biological living processes also have a broad time scale. When observing biological subcellular organelles, resolution and the speed of life activities should be considered. For the dynamic process, it’s meaningless to simply improve the spatial resolution without correspondingly increasing the imaging speed which should be no less than the movement speed of the observed object. Existing super-resolution or high-speed optical imaging is limited by the mutual constraints of spatial and time resolution, making it difficult to obtain both super-resolution and high-speed optical imaging. In order to break the constraints of this game and gain high-speed super-resolution images, the CS-SIM system combines SIM (structured illumination microscopy) and CSP (compressed sensing photography). Since they both are wide filed imaging and CSP is a passive receiving imaging technology, SIM and CSP have potential to combine closely and achieve super-resolution and highspeed imaging.","PeriodicalId":201899,"journal":{"name":"International Conference on Optical Instruments and Technology","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129232482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A new multi-spectral image registration algorithm 一种新的多光谱图像配准算法

International Conference on Optical Instruments and Technology Pub Date : 2022-07-22 DOI: 10.1117/12.2619451

Wu Kun, Bin Li, Zongxin Liu, Yifan Shen, Jing Hu

引用次数: 1

Active non-line-of-sight human pose estimation based on deep learning 基于深度学习的主动非视线人体姿态估计

International Conference on Optical Instruments and Technology Pub Date : 2022-07-22 DOI: 10.1117/12.2610975

Qianqian Xu, Liquan Dong, Lingqin Kong, Yuejin Zhao, Ming Liu

{"title":"Active non-line-of-sight human pose estimation based on deep learning","authors":"Qianqian Xu, Liquan Dong, Lingqin Kong, Yuejin Zhao, Ming Liu","doi":"10.1117/12.2610975","DOIUrl":"https://doi.org/10.1117/12.2610975","url":null,"abstract":"Non-Line-of-Sight technology is to image objects that are hidden from the camera's view. It has a wide range of application prospects in robotic vision, national defense, remote sensing, medical imaging, and unmanned driving. Active Non-Lineof- Sight imaging mainly relies on time-resolved optical impulse responses. The Non-Line-of-Sight imaging system emits ultra-short light pulses to illuminate the diffuse reflection wall, and uses ultra-fast time-resolved single-photon detectors to collect multiple reflected photon information, thereby obtaining information in the hidden scene. Finally, various reconstruction algorithms are used to reconstruct the hidden scene. However, most of the existing reconstruction algorithms have the problems of slow reconstruction speed and fuzzy reconstruction results, especially in the aspect of human pose estimation. In this article, we describe a method of active Non-Line-of-Sight human pose estimation based on deep learning. In order to solve the problem of lack of deep learning data, we simulate large amounts of pseudo-transient images for the network, including various complex actions: walking, jumping, turning, bending back and forth, rotating, using the confocal Non-Line-of-Sight imaging model. And then we train the simulated transient images using light cones Transformation and U-net coding and decoding network structure. Finally, we examine the performance of our method on synthetic and experimental datasets. The prediction results show that our method can not only estimate the pose of real measured non-view human pose data, but also significantly improve the quality of reconstruction.","PeriodicalId":201899,"journal":{"name":"International Conference on Optical Instruments and Technology","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116015193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Combination of dot-matrix lighting and floodlighting for multipath interference suppression in ToF imaging 点阵照明与泛光照明相结合抑制ToF成像中的多径干扰

International Conference on Optical Instruments and Technology Pub Date : 2022-07-22 DOI: 10.1117/12.2619673

Xiaoyue Liu, Jiayi Huo, Huimin Yan

{"title":"Combination of dot-matrix lighting and floodlighting for multipath interference suppression in ToF imaging","authors":"Xiaoyue Liu, Jiayi Huo, Huimin Yan","doi":"10.1117/12.2619673","DOIUrl":"https://doi.org/10.1117/12.2619673","url":null,"abstract":"Time-of-flight (ToF) cameras obtain the depth information of the whole scene simultaneously by floodlighting it. In the presence of mutual reflection between the targets, the measurement would suffer from the multipath interference (MPI), because the signal received by the sensor is a mixture of direct component and multipath (or global) component. MPI would lead to significant measurement errors. In this paper is introduced a method of separating the direct and global components by once dot-matrix lighting and twice floodlighting with different frequencies. With dot-matrix lighting, the depth information at the dot matrix position is almost only determined by the direct component. The phase value of the direct component is readily calculated. The global component at the dot position with floodlighting is separated by minimizing the separation error through solving the nonlinear least square problem. Then the global component of the whole scene can be obtained by two-dimensional interpolation from data at dot matrix position. As a result, the direct component can be calculated by subtracting the interpolation result from the floodlighting signal, and the depth were calculated only from direct component. Semi-physical experiments were made for three kinds of scenes, blank corner with uniform reflectivity, the corner with different reflectivity areas and the corner with an object placed in front of it. The results demonstrate that the MPI has been significantly suppressed in all scenes. Especially in the area with strong MPI in the first two kinds of scenes, the measurement errors can decrease to about 10%~20%.","PeriodicalId":201899,"journal":{"name":"International Conference on Optical Instruments and Technology","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115685900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0