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Iterative Gaussian-Laplacian Pyramid Network for Hyperspectral Image Classification

IEEE Transactions on Geoscience and Remote Sensing 2024年 62卷 1-22页

作者： Chang, Chein-I Liang, Chia-Chen Hu, Peter Fuming Information and Technology College Dalian116026 China University of Maryland Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering BaltimoreMD21250 United States National Cheng Kung University Department of Electrical Engineering Tainan70101 Taiwan University of Maryland School of Medicine R Adams Cowley Shock Trauma Center Shock Trauma Anesthesia Organized Research Center Department of Anesthesia BaltimoreMD21201 United States

Gaussian pyramid (GP) is a commonly used image coding technique that encodes an image as a pyramid that is stacked by a set of images with Gaussian window-reduced sizes and multiple spatial resolutions. Associated with GP, a Laplacian pyramid (LP) can be also constructed to represent differential images between images in two consecutive layers of GP. Such resulting Gaussian-Laplacian pyramid (GLP) performs data compression in a lossless and lossy manner. A convolutional neural network (CNN) consists of a series of layers concatenated in a feedforward manner where each layer has a convolutional sublayer (CL) and a pooling sublayer (PL). Interestingly, each layer implemented by CL and PL in a CNN can be realized by a single layer in GP in the sense that CL and PL can be carried out by a low-pass Gaussian filter operated as a Gaussian kernel in a single layer of GP. This article develops a new approach to hyperspectral image classification (HSIC), called the GLP network (GLPN), which uses not only GP to realize CNN but also LP to capture differential information between two consecutive layers that CNN cannot. Furthermore, by incorporating an iterative process into GLPN, we can derive an iterative GLPN (IGLPN) that can be considered a companion of a recently developed iterative random training sampling CNN (IRTS-CNN) by replacing CNN with GLPN. Since GLPN can realize CNN in a better way, it is expected that IGLPN will perform better than IRTS-CNN and also significantly reduce computational efficiency compared to IRTS-CNN. © 1980-2012 IEEE.

关键词： Iterative methods

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Editorial: Introduction to the special issue on advances in radar technology

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Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University 2021年第2期48卷 1-6页

作者： Liu, Hongwei Shui, Penglang Kong, Lingjiang Wei, Yinsheng Liu, Yongxiang Wang, Yu Li, Gang Chen, Bo National Laboratory of Radar Signal Processing Xidian University Xi'an710071 China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China School of Electronics and Information Engineering Harbin Institute of Technology Harbin150001 China College of Intelligence Science National University of Defense Technology Changsha410073 China Institute of Aerospace Information Innovation Chinese Academy of Sciences Beijing100864 China Department of Electronic Engineering Tsinghua University Beijing100084 China

雷达历经了80多年的发展,如今已成为重要的信息传感器之一,在国防领域具有战略性地位,在民用领域也得到越来越广泛的应用。随着软硬件相关技术的快速发展,现代雷达已经不仅仅局限于高功率、高分辨、多波段等传统的性能提升和功能扩展,... 详细信息

雷达历经了80多年的发展,如今已成为重要的信息传感器之一,在国防领域具有战略性地位,在民用领域也得到越来越广泛的应用。随着软硬件相关技术的快速发展,现代雷达已经不仅仅局限于高功率、高分辨、多波段等传统的性能提升和功能扩展,且更多聚焦于信号处理的精细化、信息处理的智能化、单一平台功能的多样化和集成化、多平台的网络化与协同化、器件发展的小型化和片上化、服务界面的便利化和人性化等,使其应用日益广泛。为此,《西安电子科技大学学报》组织了"雷达技术进展"专题,共录用23篇论文,包括目标识别、目标检测与跟踪、雷达成像、电子对抗、协同组网等方向,分别介绍如下。

关键词：雷达信息传感器国防领域

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BIRNAT: Bidirectional Recurrent Neural Networks with Adversarial Training for Video Snapshot Compressive Imaging 1

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16th European Conference on Computer Vision, ECCV 2020

作者： Cheng, Ziheng Lu, Ruiying Wang, Zhengjue Zhang, Hao Chen, Bo Meng, Ziyi Yuan, Xin National Laboratory of Radar Signal Processing Xidian University Xi’an China Beijing University of Posts and Telecommunications Beijing China New Jersey Institute of Technology NewarkNJ United States Nokia Bell Labs Murray HillNJ United States

ISBN: (数字)9783030585860

ISBN: (纸本)9783030585853

We consider the problem of video snapshot compressive imaging (SCI), where multiple high-speed frames are coded by different masks and then summed to a single measurement. This measurement and the modulation masks are fed into our Recurrent Neural Network (RNN) to reconstruct the desired high-speed frames. Our end-to-end sampling and reconstruction system is dubbed BIdirectional Recurrent Neural networks with Adversarial Training (BIRNAT). To our best knowledge, this is the first time that recurrent networks are employed to SCI problem. Our proposed BIRNAT outperforms other deep learning based algorithms and the state-of-the-art optimization based algorithm, DeSCI, through exploiting the underlying correlation of sequential video frames. BIRNAT employs a deep convolutional neural network with Resblock and feature map self-attention to reconstruct the first frame, based on which bidirectional RNN is utilized to reconstruct the following frames in a sequential manner. To improve the quality of the reconstructed video, BIRNAT is further equipped with the adversarial training besides the mean square error loss. Extensive results on both simulation and real data (from two SCI cameras) demonstrate the superior performance of our BIRNAT system. The codes are available at https://***/BoChenGroup/BIRNAT. © 2020, Springer Nature Switzerland AG.

关键词： Recurrent neural networks

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Clutter cancellation in passive radar from the perspective of maximum likelihood

Clutter cancellation in passive radar from the perspective o...

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IEEE International Conference on radar

作者： Xiaoyong Lyu Jin Xu Jun Wang School of Information Engineering Zhengzhou University Zhengzhou China The 38th research Institute of China electronics technology group corporation Hefei China National Laboratory of Radar Signal Processing Xidian University Xi'an China

ISBN: (纸本)9781665468893

Clutter cancellation in passive radar is gaining increasing interest. The extensive cancellation algorithm (ECA) has received a range of applications in passive radar clutter cancellation. However, the ECA suffers from great computational complexity. Several variants of ECA have been proposed to increase the computational efficiency. Among those methods, a parallel implementation algorithm obtains an interesting conclusion that, the cancellation weight vector of ECA can be calculated as the weighted mean of several weight vectors, each of which is computed using only a small segment of the reference and surveillance signals. The algorithm can get very similar cancellation weight vector compared with the ECA, but increases the computational efficiency. However, the derivation of this algorithm in the original paper is very complicated and not straightforward to be understood and the obtaining of the final conclusion is not explicit. In this paper, we rederive this algorithm from the maximum likelihood (ML) perspective. We can get the same algorithm, but use a very simple and straightforward derivation. Furthermore, we show explicitly how the finial conclusion is derived, by making some assumptions on the statistical characteristics of the illuminating signal, which is not discussed in the original paper. Finally, we analyze through simulations how the assumptions made on the illuminating signal affect the estimation of the cancellation weight vector.

关键词： Passive radar Maximum likelihood estimation radar clutter Surveillance Broadcasting Computational efficiency Autocorrelation

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Design of three-dimensional gesture recognition and motion tracking human-computer intelligent interaction system based on PAJ7620

Design of three-dimensional gesture recognition and motion t...

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2021 International Conference on Information technology and Intelligent Control, CITIC 2021

作者： Wang, Jian-Liang Wei, Ye Li, Yang Meng, Yuan Li, Ming-Yu Xu, Jiang-Yan Jiao, Wan-Ming Ban, Lan Liu, Jun-Pei Zhang, Hong-Feng Zhang, Wei Wang, Li-Na Luo, Fu-Chen Wang, Yu-Duo Tianjin College University of Science and Technology Beijing Tianjin China Civil Aviation University of China Tianjin Key Laboratory of Intelligent Signal and Image Processing Tianjin China Tianjin Normal University Tianjin Key Laboratory of Wireless Mobile Communication and Radio Energy Transmission Tianjin China Binhai College Nankai University Tianjin China Tianjin Tianshi College Tianjin China

With the increasing degree of informatization and intelligence in modern society, human-computer interaction technology has become one of the commonly used scientific and technological achievements. "Gesture" can be used as inputing image information, and make more intuitive and convenient for perception of user interface. To a certain extent, it can complete the intelligent interaction function between human and computer. The design is a human-computer intelligent interaction system for 3D gesture recognition and motion tracking based on gesture sensor PAJ7620. STM32 chip is used as the main control unit to recognize accurately, analyze and process different gestures collected by the gesture sensor, and control the OLED screen to display the gesture information. It can further drive the carrier to take corresponding actions and realize the intelligent human-computer interaction recognition of gestures. The experimental test results show that the recognition rate is lose to 100% when the distance is within 10cm. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Gesture recognition

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X-Band Polinsar Vegetation Canopy Height Inversion Strategy Based on Frequency Segmentation

X-Band Polinsar Vegetation Canopy Height Inversion Strategy ...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Fanyi Tang Jinwei Xie Zhiyong Suo Han Li Zhenfang Li National Laboratory of Radar Signal Processing Xidian University Xi'an China Nanjing Research Institute of Electronic Technology China

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

Vegetation canopy height inversion is a significant research content in Polarimetric Interferometry Synthetic Aperture radar (PolInSAR) surface parameter inversion. One practical challenge is that the traditional three-stage inversion method will lead to the inaccurate inversion of vegetation canopy height in X-band because of the too concentrated distribution of polarization interference coherence coefficients (PolInCc). In this paper, an X-band PolInSAR vegetation canopy height inversion strategy is proposed based on Frequency Segmentation (FS). The FS divides the original PolInSAR images into multiple PolInSAR images called sub-images, and the sub-images are used to estimate the more near-linear PolInCc distribution of the sub-images by interferometry. Then the precise terrain phase and effective volume coherence coefficient can be obtained to invert the vegetation canopy height accurately. The validity of the proposed method is verified by N-SAR X-band real data.

关键词： Vegetation mapping Scattering Azimuth Coherence Fitting Interferometry Extinction coefficients

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Research on Coordinated Coverage of Non-Lambertian Optical Wireless Communications 7

Research on Coordinated Coverage of Non-Lambertian Optical W...

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7th International Conference on Computer and Communications, ICCC 2021

作者： Ding, Jupeng Chih-Lin, I. Wang, Jintao Yang, Hui Wang, Lili Xinjiang University Key Laboratory of Signal Detection and Processing In Xinjiang Uygur Autonomous Region School of Information Science and Engineering Ürümqi China China Mobile Research Institute Beijing China Tsinghua University Beijing National Research Center For Information Science and Technology Department of Electronic Engineering Beijing China Ludong University School of Information and Electrical Engineering Yantai China

ISBN: (纸本)9781665409506

To a large extent, the performance of wireless optical communication system is affected by the light source radiation characteristics. Previous works are limited to rotationally symmetric Lambertian beam configurations, which fail to support target location oriented coordinated coverage. Different from the existing research, this paper proposes a coordinated coverage enhancement scheme based on asymmetric non-Lambertian optical beam configuration. Without loss of generality, this paper presents numerical analysis of coordinated and non-coordinated coverage performance in typical medium-sized indoor application scenario. Compared with non-coordinated coverage, the numerical results illustrate that the proposed coordinated coverage scheme could introduce about 4.08 dB SNR gain without transmission power increase. Therefore, non-Lambertian beam cooperation should be viewed as one efficient wireless optical communication technology. © 2021 IEEE.

关键词： Light sources

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Continuous Distributed processing of Software Defined radar

Continuous Distributed Processing of Software Defined Radar

引用

IEEE International Conference on radar

作者： Bing Li Qiang Qiu Shiqi Gong Yongjun Liu Yu Lei CAS Key Lab of Network Data Science and Technology Chinese Academy of Sciences Institute of Computing Technology Beijing China State Key Laboratory of Internet of Things for Smart City University of Macau Macau China National Laboratory of Radar Signal Processing Xidian University Xi'an China Golaxy Data Technology Co. Ltd. Beijing China

ISBN: (纸本)9781665468893

Software-defined radar has been an active research field for more than ten years. However, the low performance and low scalability of the traditional processing techniques of SDR make it hard to deal with complex radar tasks. The stream processing engine is a software that supports low latency and high scalability distributed data processing. It is widely used in log, image, and video processing scenarios but rarely used in radar applications. This paper reviews processing software-defined radar data by using the stream processing engine, and we illustrate the differences between processing log data and radar data. Furthermore, we discuss some optimizations for stream processing engines to get better performance in the radar data processing.

关键词： Protocols Scalability Streaming media radar imaging Data processing Software Hardware

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Novel explanation of the Active Galactic Nuclei. The Power Source of Quasars as a result of vacuum polarization by the gravitational singularities on the distributional BHs horizon 9

Novel explanation of the Active Galactic Nuclei. The Power S...

引用

9th International Conference on Mathematical Modeling in Physical sciences, IC-MSQUARE 2020

作者： Foukzon, Jaykov Men'Kova, Elena R Potapov, Alexander A Department of Mathematics Israel Institute of Technology Haifa3200003 Israel All-Russian Research Institute for Optical and Physical Measurements Moscow119361 Russia Kotelnikov Institute of Radioengineering and Electronics of the Russian Academy of Sciences Moscow125009 Russia JNU-IREE Joint Laboratory of Fractal Method and Signal Processing Department of Electronic Engineering College of Information Science and Technology Jinan University Guangzhou China

In this paper we argue that the current paradigm for AGN and quasars is essentially incomplete and a rivision is needed. Remind that the current paradigm for AGN and quasars is that their radio emission is explained by synchrotron radiation from relativistic electrons that are Doppler boosted through bulk motion. In this model, the intrinsic brightness temperatures cannot exceed 1011 to 1012 K. Typical Doppler boosting is expected to be able to raise this temperature by a factor of 10. The observed brightness temperature of the most compact structures in BL Lac, constrained by baselines longer than 5.3G, must indeed exceed 2 × 1013K and can reach as high as 3 × 1014K. This is difficult to reconcile with current incoherent synchrotron emission models from relativistic electrons, requiring alternative models such as emission from relativistic protons. However the proton, as we know, is 1836 times heavier than an electron and absolutely huge energy is required to accelerated it to sublight speed. These alternative models such as emission from relativistic protons can be suported by semiclassical gravity effect finds its roots in the singular behavior of quantum fields on curved distributional space- times presented by rotating gravitational singularities. © Published under licence by IOP Publishing Ltd.

关键词： Synchrotron radiation

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One to multiple mapping dual learning: Learning multiple sources from one mixed signal

arXiv

引用

arXiv 2021年

作者： Liu, Ting Wang, Wenwu Zhang, Xiaofei Yan, Jingwen Guo, Yina The Department of Electronics and Communication Engineering Taiyuan University of Science and Technology Taiyuan030024 China The Centre for Vision Speech and Signal Processing University of Surrey Guildford SurreyGU2 7XH United Kingdom The Guangdong Provincial Key Laboratory of Digital Signal and Image Processing Technology

Single channel blind source separation (SCBSS) refers to separate multiple sources from a mixed signal collected by a single sensor. The existing methods for SCBSS mainly focus on separating two sources and have weak generalization performance. To address these problems, an algorithm is proposed in this paper to separate multiple sources from a mixture by designing a parallel dual generative adversarial Network (PDualGAN) that can build the relationship between a mixture and the corresponding multiple sources to realize one-to-multiple cross-domain mapping. This algorithm can be applied to any mixed model such as linear instantaneous mixed model and convolutional mixed model. Besides, one-to-multiple datasets are created which including the mixtures and corresponding sources for this study. The experiment was carried out on four different datasets and tested with signals mixed in different proportions. Experimental results show that the proposed algorithm can achieve high performance in peak signal-to-noise ratio (PSNR) and correlation, which outperforms state-of-the-art algorithms. © 2021, CC BY.

关键词： Mapping

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