2017 IEEE International Conference on Imaging Systems and Techniques (IST)最新文献_第2页

Leaf moisture content measurement using polarized active imaging LiDAR 利用偏振主动成像激光雷达测量叶片含水量

2017 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2017-10-01 DOI: 10.1109/IST.2017.8261557

Xinhao Xie, Lijun Xu, Xiaolu Li

{"title":"Leaf moisture content measurement using polarized active imaging LiDAR","authors":"Xinhao Xie, Lijun Xu, Xiaolu Li","doi":"10.1109/IST.2017.8261557","DOIUrl":"https://doi.org/10.1109/IST.2017.8261557","url":null,"abstract":"In this paper, a polarized active imaging technology was utilized for measuring the moisture content of the holly leaves. Polarization images of the holly leaves encoded with the polarization degree were acquired by the polarized active imaging LiDAR. The polarization degree of the holly leaves was used as a variable to generate a mapping model to reflect the moisture content. The polarization degrees were calculated from polarization images matched by the method of Speeded Up Robust Feature (SURF) algorithm and affine transformation. Images were denoised by using the multiple iterative median filter and the Lee filter. The actual moisture contents of the holly leaves were obtained by the method of moisture drying processing. The predictive accuracy and stabilities were utilized to establish an optimal mapping model by the method of statistical fitting. Experiments were carried out to validate the mapping model between the moisture content and the polarization degree of the holly leaves. The results show that the polarization degrees of the holly leaves are significantly positive-correlated with the moisture content rising from 45% to 75%. The relationship between the moisture content and the polarization degree of the holly leaves was presented with exponential model.","PeriodicalId":187213,"journal":{"name":"2017 IEEE International Conference on Imaging Systems and Techniques (IST)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125744291","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

Joint of discrete curvelet transform and nonlocal tensor sparse regularization for SAR image despeckling 基于离散曲线变换和非局部张量稀疏正则化的SAR图像去噪

2017 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2017-10-01 DOI: 10.1109/IST.2017.8261454

Gao Chen, Gang Li

{"title":"Joint of discrete curvelet transform and nonlocal tensor sparse regularization for SAR image despeckling","authors":"Gao Chen, Gang Li","doi":"10.1109/IST.2017.8261454","DOIUrl":"https://doi.org/10.1109/IST.2017.8261454","url":null,"abstract":"This paper proposes a new joint sparsity regularization model (JSRM) for synthetic aperture radar (SAR) image despeckling by characterizing local sparsity and nonlocal self-similarity of SAR images simultaneously. The proposed model contains a data fidelity term and two regularization terms. One of the two regularization terms employs the discrete curvelet transform to depict the local smoothness of the SAR image, and the other one employs a tensor sparse transform of the three-dimensional (3D) tensor generated by stacking similar SAR image patches. The joint employment of these two regularization terms, which has not been utilized in existing methods of SAR image despeckling yet, aims to produce better despeckling performance and preserve more geometrical features of SAR images. To address the optimization problem in the proposed model, a new efficient algorithm is derived based on the split Bregman iterations framework. Experimental results show that the proposed model considerably outperforms some conventional and state-of-the-art techniques in terms of both subjective visual assessment of image quality and objective evaluation.","PeriodicalId":187213,"journal":{"name":"2017 IEEE International Conference on Imaging Systems and Techniques (IST)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132646676","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

Precise multi-channel timing analysis system for multi-stop LIDAR correlation 用于多站激光雷达相关的精密多通道时序分析系统

2017 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2017-10-01 DOI: 10.1109/IST.2017.8261560

E. Arabul, Ayoub Girach, J. Rarity, N. Dahnoun

{"title":"Precise multi-channel timing analysis system for multi-stop LIDAR correlation","authors":"E. Arabul, Ayoub Girach, J. Rarity, N. Dahnoun","doi":"10.1109/IST.2017.8261560","DOIUrl":"https://doi.org/10.1109/IST.2017.8261560","url":null,"abstract":"The development of single photon applications has led to significant research into high-precision timing analysis systems. The requirement of precise time-of-flight measurements, as well as the removal of ambient/dark photon noise has been a driving force in the development of systems which provide a precise timing resolution. The proposed system aims to compute time-of-flight single photon measurements for a Multi-stop Light Detection and Ranging (LIDAR) experiment. This involves precisely computing time-of-flight between an emitted START signal and multiple photon reflections corresponding to STOP signals within a Field Programmable Gate Array (FPGA). The aim of this system is to time-tag photon counts from multiple single photon detectors with a resolution in the tens of picoseconds, where correlation computations are performed in hardware to determine time-of-flight between START and STOP signals. The developed system showed an 8-channel multi-stop timing analysis system and achieved an average resolution of 21.5 ps, with a measurement error of 20 ps Full Width Half Maximum (FWHM). The number of STOPs that can be detected by the system is determined by the deadtime and dynamic range of the TDC. In our design the dynamic range is 2.14 s and the deadtime for each TDC block is 8 ns. From the tests conducted on the time-tag correlator, the capability to record 120 STOPs has been observed.","PeriodicalId":187213,"journal":{"name":"2017 IEEE International Conference on Imaging Systems and Techniques (IST)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114692643","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: 10

Blur image classification based on deep learning 基于深度学习的模糊图像分类

2017 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2017-10-01 DOI: 10.1109/IST.2017.8261503

Rui Wang, Wei Li, Runnan Qin, Jinzhong Wu

{"title":"Blur image classification based on deep learning","authors":"Rui Wang, Wei Li, Runnan Qin, Jinzhong Wu","doi":"10.1109/IST.2017.8261503","DOIUrl":"https://doi.org/10.1109/IST.2017.8261503","url":null,"abstract":"Blur type identification is significant for blind image recovery in image processing area. In this paper, an accurate classification system exploiting Convolution Neural Network (CNN) is designed to identify four blur types of images: defocus blur, Gaussian blur, haze blur and motion blur. A supervised learning model of Simplified-Fast-Alexnet (SFA), which is an abbreviated and modified version of Alexnet, is created to map the input images into a higher dimensional feature space, in which the blurs can be classified accurately. With proportional compressing the output number of each convolution layer in Alexnet by the ratio of 0.5 and removing the first two Full Connected layers (FCs) in Alexnet, the SFA successfully simplifies the Alexnet and overcomes the fatal disadvantage of parameter redundancy. Moreover, the batch normalization layers are added into the designated classifier to replace the dropout method, thus it can accelerate the convergence rate of deep network during the training stage by reducing internal covariate shift as well as alleviate the overfitting problem. Experiments demonstrate the remarkable performance of the suggested approach in comparison with the original Alexnet and the state-of-the-art on the frequently-used Berkeley dataset and Pascal VOC 2007 dataset.","PeriodicalId":187213,"journal":{"name":"2017 IEEE International Conference on Imaging Systems and Techniques (IST)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117109000","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: 18

An INS-aided GPS fast acquisition algorithm for high dynamic applications 一种用于高动态应用的GPS辅助快速采集算法

2017 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2017-10-01 DOI: 10.1109/IST.2017.8261487

Falin Wu, Shan Xu, Zhendian Wu, Jiemin Chen

引用次数: 0

A pen locating scheme for large-size electronic whiteboards 一种大型电子白板笔定位方案

2017 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2017-10-01 DOI: 10.1109/IST.2017.8261444

Wenjie Zhou, Xiaohui Duan

引用次数: 0

A study of image segmentation algorithms combined with different image preprocessing methods for thyroid ultrasound images 结合不同图像预处理方法的甲状腺超声图像分割算法研究

2017 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2017-10-01 DOI: 10.1109/IST.2017.8261449

Junying Chen, Fengmin Li, Yixuan Fu, Qun Liu, Jiajun Huang, Kai Li

引用次数: 6

An optimized layout method based on genetic algorithm for DPOS 基于遗传算法的DPOS优化布局方法

2017 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2017-10-01 DOI: 10.1109/IST.2017.8261480

Xiaolin Gong, Haojie Liu, Gang Liu, Xiaolu Li

引用次数: 6

Application of self-adaptive generalized predictive control in the spinning process of absorbable suture (Key laboratory of Tianjin modern electromechanical equipment technology) 自适应广义预测控制在可吸收缝线纺丝过程中的应用(天津市现代机电装备技术重点实验室)

2017 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2017-10-01 DOI: 10.1109/IST.2017.8261562

X. Sui, Deming Wang, Yang Zhang, Shuo Wang, Yao Li

引用次数: 0

An image processing approach for characterizing working frequency of pulse combustion 一种表征脉冲燃烧工作频率的图像处理方法

2017 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2017-10-01 DOI: 10.1109/IST.2017.8261563

Fangyan Li, Lijun Xu

引用次数: 1