International Symposium on Multispectral Image Processing and Pattern Recognition最新文献_第4页

3D target detection of Geiger mode APD array lidar image 盖革模式APD阵列激光雷达图像的三维目标检测

International Symposium on Multispectral Image Processing and Pattern Recognition Pub Date : 2020-02-14 DOI: 10.1117/12.2541902

Tianming Zhao, J. Tian, Hang Liu, Peng Jiang

{"title":"3D target detection of Geiger mode APD array lidar image","authors":"Tianming Zhao, J. Tian, Hang Liu, Peng Jiang","doi":"10.1117/12.2541902","DOIUrl":"https://doi.org/10.1117/12.2541902","url":null,"abstract":"The Geiger mode Avalanche Photo Diode (APD) array lidar is a non-scanning lidar, which has a small volume, fast imaging speed and high sensitivity. In the paper, the 3D target detection of Geiger mode APD array lidar image is studied. Geiger mode APD array lidar has great noise in the process of imaging due to its imaging characteristics. The paper analyzes its noise characteristics and decomposes the noise into four parts: environment noise, loss noise, internal noise and crosstalk noise. According to the noise characteristics, the paper simulated the Geiger-mode APD array lidar imaging. And based on this, the target detection algorithm was studied. The paper proposes a filtering method based on the KNN classification and combine an improved loop filtering algorithm to preprocess the image. And then an adaptive superposition algorithm is proposed to fuse the preprocessed multi-frame image. Testing the target detection algorithm on five image data captured by the Geiger mode APD array lidar, the medium-scale and small-scale targets can be detected in 20 frames. The largescale targets can be detected in 50 frames, and long-distance targets can be detected in 100 frames.","PeriodicalId":384253,"journal":{"name":"International Symposium on Multispectral Image Processing and Pattern Recognition","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122916230","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: 2

Synthetic aperture remove occlusion algorithm based on microlens array light field imaging 基于微透镜阵列光场成像的合成孔径去遮挡算法

International Symposium on Multispectral Image Processing and Pattern Recognition Pub Date : 2020-02-14 DOI: 10.1117/12.2538182

Wentong Qian, Hui Li, Yuntao Wu

引用次数: 0

G-CNN type recognition of typical aircraft based on target characteristics 基于目标特征的典型飞机G-CNN类型识别

International Symposium on Multispectral Image Processing and Pattern Recognition Pub Date : 2020-02-14 DOI: 10.1117/12.2537974

Jiaxing Mao, Hao Dou, J. Tian

{"title":"G-CNN type recognition of typical aircraft based on target characteristics","authors":"Jiaxing Mao, Hao Dou, J. Tian","doi":"10.1117/12.2537974","DOIUrl":"https://doi.org/10.1117/12.2537974","url":null,"abstract":"This paper is aimed at the type recognition of aircraft, with four kinds of typical military aircraft as research objects. In this paper, we establish a database on aircraft type and propose an effective and efficient method of type recognition called Geometric-Convolutional Neutral Networks(G-CNN) in a coarse-to-fine manner. We start with target characteristics for the first time and establish a target characteristics database by analyzing the acquired characteristics such as geometric characteristics and optical characteristics. Next, aiming at the problem that the dataset on aircraft types is few, we build 3D models based on the characteristics database and make an aircraft type dataset using 3D simulation creatively, which is of great significance for the research on aircraft type recognition. Finally, we extract the geometric characteristics of the aircraft—affine invariant moments and aspect ratios, realizing a fast and efficient region selecting; we improve residual blocks with dilated convolution, which is used for type recognition for the first time. Our method achieves 89.0%mAP and the experiments show that it tackles the type recognition problems with improved performance.","PeriodicalId":384253,"journal":{"name":"International Symposium on Multispectral Image Processing and Pattern Recognition","volume":"215 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132627290","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: 2

Performance evaluation of SIFT under low light contrast 弱光对比度下SIFT的性能评价

International Symposium on Multispectral Image Processing and Pattern Recognition Pub Date : 2020-02-14 DOI: 10.1117/12.2535592

Hao Wang, Songzhi Jin, Xiaodan Wei, Cong Zhang, Ruiguang Hu

引用次数: 2

Crop extraction based on ultra-simple neural network modeling in the normalized rgb and CIE L*a*b* color spaces 基于归一化rgb和CIE L*a*b*色彩空间的超简单神经网络建模的作物提取

International Symposium on Multispectral Image Processing and Pattern Recognition Pub Date : 2020-02-14 DOI: 10.1117/12.2541856

Lei Hu, Xiaodong Bai, Aiping Yang, Kun Zhang, Chonghua Zhang, Bo Liu

引用次数: 2

Anti-occlusion target tracking algorithm based on template filtering 基于模板滤波的抗遮挡目标跟踪算法

International Symposium on Multispectral Image Processing and Pattern Recognition Pub Date : 2020-02-14 DOI: 10.1117/12.2541594

Wangrong Cheng, C. Xu, J. Tian

引用次数: 0

Infrared and terahertz integration detection based on optical antennas 基于光学天线的红外与太赫兹集成探测

International Symposium on Multispectral Image Processing and Pattern Recognition Pub Date : 2020-02-14 DOI: 10.1117/12.2538578

Jun Luo, D. Wei, Chai Hu, Xinyu Zhang, C. Xie

{"title":"Infrared and terahertz integration detection based on optical antennas","authors":"Jun Luo, D. Wei, Chai Hu, Xinyu Zhang, C. Xie","doi":"10.1117/12.2538578","DOIUrl":"https://doi.org/10.1117/12.2538578","url":null,"abstract":"So far, how to acquire an effective method of integration detection covering a relatively wide wavelength range has become a hot topic in the field of high performance radiation detection. In this work, the microstructure patterned Schottky-typed optical antenna is designed and then fabricated on Gallium Arsenide substrate and further used to sense near-infrared lights and terahertz signals, respectively. The wide frequency terahertz waves generated by InAs crystal are measured through patterned optical antenna device, and then the characteristics of transmitted waves are analyzed, it should be noted that the time delay characteristics of transmitted terahertz signals between 5ps and 8ps are different from microstructure patterned optical antenna. Under the conditions of using near-infrared lasers and also adjusting main parameters such as the exposure time, for example, 0.04ms、0.4ms、0.6ms、0.8ms、1.0ms and 1.5ms, in the experiments, the transmitted image characters acquired using functioned optical antennas with different electrode patterns, are analyzed. In the near-infrared transmission experiments, the transmitted bright light points or spots with relatively large distribution density and high intensity and very small structural size (~1μm), are discovered, which distribute over the top layer of electrode zone without metal structures of optical antenna device. The developed detection architecture based on Schottky-typed functioned optical antennas to sense infrared light and terahertz radiation, is expected to integrated sense electromagnetic signals in wide spectrum regime.","PeriodicalId":384253,"journal":{"name":"International Symposium on Multispectral Image Processing and Pattern Recognition","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133071830","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

Discussion on the surface rupture in the south segment of the Minjiang fault inferred from remote sensing images 基于遥感影像的岷江断裂南段地表破裂探讨

International Symposium on Multispectral Image Processing and Pattern Recognition Pub Date : 2020-02-14 DOI: 10.1117/12.2539314

Q. Jia, Huaguo Liu, Feng Li

引用次数: 1

Accurate segmentation of bladder wall and tumor regions in MRI using stacked dilated U-Net with focal loss 在MRI中使用叠置扩张U-Net精确分割膀胱壁和肿瘤区域

International Symposium on Multispectral Image Processing and Pattern Recognition Pub Date : 2020-02-14 DOI: 10.1117/12.2538323

Hong Pan, Ziqiang Li, Runqiu Cai, Yaping Zhu

{"title":"Accurate segmentation of bladder wall and tumor regions in MRI using stacked dilated U-Net with focal loss","authors":"Hong Pan, Ziqiang Li, Runqiu Cai, Yaping Zhu","doi":"10.1117/12.2538323","DOIUrl":"https://doi.org/10.1117/12.2538323","url":null,"abstract":"Automatic and accurate segmentation of bladder walls and tumors in magnetic resonance imaging (MRI) is a challenging task, due to significant bladder shape variations, strong intensity inhomogeneity in urine and very high variability across tumors appearance. To tackle such issues, we propose to leverage the representation capacity of an improved U-Net networks using stacked dilated convolutions. The proposed structure includes stacked dilated convolutions to increase the receptive field without incurring gridding artifacts. In addition, we embed stacked dilated convolution network into the U-Net architecture, thus enabling extracting multi-scale features for segmentation of multi structures with different shapes and scales. Finally, we apply a focal loss function to make all classes contribute equally to the loss function in our model. Evaluations on T2-weighted MRI show the proposed model achieves a higher level of accuracy than state-of-the-art methods, with a mean Dice similarity coefficient of 0.95, 0.81 and 0.66 for inner wall, outer wall and tumor region segmentation, respectively. These results demonstrate a strong agreement with reference standards and a high performance gain compared with existing methods.","PeriodicalId":384253,"journal":{"name":"International Symposium on Multispectral Image Processing and Pattern Recognition","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129663523","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

Cloud bottom height estimation methods for optical imaging terminal guidance 光学成像末制导的云底高度估计方法

International Symposium on Multispectral Image Processing and Pattern Recognition Pub Date : 2020-02-14 DOI: 10.1117/12.2535716

Shuai Liang, Mengying Liu, Zhongyang Wang, Tianxu Zhang

{"title":"Cloud bottom height estimation methods for optical imaging terminal guidance","authors":"Shuai Liang, Mengying Liu, Zhongyang Wang, Tianxu Zhang","doi":"10.1117/12.2535716","DOIUrl":"https://doi.org/10.1117/12.2535716","url":null,"abstract":"We use domestic and foreign meteorological satellite data to carry out the research of Operational Regional meteorology which can be used for optical imaging terminal guidances. Attacks on areas covered by clouds can be divided into the following two scenarios: 1. Clouds are medium-high clouds, because the cloud base height of this kind of cloud layer is relatively high, generally more than 2500 meters, it will not have much influence on the optical imaging terminal guidance; 2. With low cloud coverage but not completely covered, the cloud can be detected and segmented, avoiding the cloud to hit the target. We use machine learning algorithm training model to divide the cloud into multi-layer cloud and single layer cloud, and the classification accuracy reaches 82.1%. Then for single-layer clouds, there are two methods to estimate the cloud bottom height: 1. We can use the MODIS data of the Aqua meteorological satellite to identify clouds of different attributes for cloud height estimation. 2. The height of single layer clouds can be calculated directly by using the physical characteristics of clouds, the average calculation error is 16.5%.","PeriodicalId":384253,"journal":{"name":"International Symposium on Multispectral Image Processing and Pattern Recognition","volume":"11430 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129564115","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