Iet Optoelectronics最新文献_第9页

Parallax Refinement Network Based on Adaptive Convolution 基于自适应卷积的视差细化网络

IF 1.6 4区计算机科学

Iet Optoelectronics Pub Date : 2022-01-01 DOI: 10.12677/oe.2022.124017

文辉胡

引用次数: 0

Progress on the Non-Destructive Determination of Quality in Bayberry Fruit 杨梅果实品质无损检测研究进展

IF 1.6 4区计算机科学

Iet Optoelectronics Pub Date : 2022-01-01 DOI: 10.12677/oe.2022.121003

力凡游

引用次数: 0

The Study of Illumination for Table Tennis Venue Influenced by Illumination Design Based on Taguchi Method 基于田口法的乒乓球场地照明设计影响研究

IF 1.6 4区计算机科学

Iet Optoelectronics Pub Date : 2022-01-01 DOI: 10.12677/oe.2022.121005

至知王

引用次数: 0

Design and Implementation of Digital Electronic Ballasts for Ultra-High Pressure Mercury Lamps 超高压汞灯数字式电子镇流器的设计与实现

IF 1.6 4区计算机科学

Iet Optoelectronics Pub Date : 2022-01-01 DOI: 10.12677/oe.2022.124018

鹏赵

引用次数: 0

Research Status of Cavity Masks for Mid-Infrared Semiconductor Lasers 中红外半导体激光器的腔掩模研究现状

IF 1.6 4区计算机科学

Iet Optoelectronics Pub Date : 2022-01-01 DOI: 10.12677/oe.2022.122008

乐刘

引用次数: 0

Study on the Influence of Nonlinearity and Chirp on Propagation Properties of Airy Pulse 非线性和啁啾对艾里脉冲传播特性影响的研究

IF 1.6 4区计算机科学

Iet Optoelectronics Pub Date : 2022-01-01 DOI: 10.12677/oe.2022.124016

兆启李

引用次数: 0

Development of Three-Phase Three Wire Active Power Filter based on Proportional Integral Control Strategy 基于比例积分控制策略的三相三线有源电力滤波器的研制

IF 1.6 4区计算机科学

Iet Optoelectronics Pub Date : 2022-01-01 DOI: 10.12677/oe.2022.123014

继锋吴

引用次数: 0

Single-layer tri-state switching as an economical method to address linear light-emitting diode arrays 单层三态开关是解决线性发光二极管阵列的一种经济方法

IF 1.6 4区计算机科学

Iet Optoelectronics Pub Date : 2021-12-22 DOI: 10.1049/ote2.12061

Eric Klein, Patrick Ruther, Oliver Paul

{"title":"Single-layer tri-state switching as an economical method to address linear light-emitting diode arrays","authors":"Eric Klein, Patrick Ruther, Oliver Paul","doi":"10.1049/ote2.12061","DOIUrl":"10.1049/ote2.12061","url":null,"abstract":"This paper reports on new schemes based on the concept of tri-state switching for routing linear arrays of light-emitting diodes (LEDs) on slim substrates. The schemes use a minimal number of wires in single-metal planar technologies, where wires are not allowed to cross. They have in common that the number of LEDs, NL, addressable by NW wires is given by NL = 4NW − 6. The designs are built on a family of hierarchically interconnected structures with (2n+1 − 2) LEDs and (2n−1 + 1) wires, for positive integers n. A process termed linear expansion straightforwardly extends them to arbitrary values of NW and adds 4 LEDs with each additional wire. Expressions for series resistances and the average wire length normalized to the array length are derived. In hierarchical designs, the average normalized wire length asymptotically approaches 7/12 for large n. A matrix formulation graphically elucidates the new interconnection schemes.","PeriodicalId":13408,"journal":{"name":"Iet Optoelectronics","volume":"16 3","pages":"106-115"},"PeriodicalIF":1.6,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/ote2.12061","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48235005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Infrared small target detection algorithm based on spatial dissimilarity weighted local contrast 基于空间不相似度加权局部对比度的红外小目标检测算法

IF 1.6 4区计算机科学

Iet Optoelectronics Pub Date : 2021-12-10 DOI: 10.1049/ote2.12062

Zhonghua Wang, Siwei Duan

{"title":"Infrared small target detection algorithm based on spatial dissimilarity weighted local contrast","authors":"Zhonghua Wang, Siwei Duan","doi":"10.1049/ote2.12062","DOIUrl":"10.1049/ote2.12062","url":null,"abstract":"To solve the problem that the local contrast algorithm is easily influenced by the heavy clutter background or strong noise and does not fully consider the spatial neighbourhood characteristics of the small target, a spatial dissimilarity weighted local contrast-based method (SDWLCM) for infrared small target detection is proposed in this paper. Firstly, the two-dimensional difference of the Gaussian filter with central excitation and lateral suppression characteristics is chosen to preprocess the original infrared image for removing the flat background and improving the signal-to-noise ratio (SNR) of the small target. Secondly, the spatial dissimilarity between the target and its surrounding backgrounds is designed for local contrast weighting to generate the contrast saliency map so that the heavy clutter background is greatly suppressed and the small target is further highlighted. Thirdly, the saliency map is segmented by the adaptive threshold to get the real targets. Experimental results show that, compared with other methods, the SDWLCM, which owns not only a higher SNR gain and a larger background suppression factor but also a higher detection rate and a lower false alarm rate, is confirmed to be an effective method to detect the small targets.","PeriodicalId":13408,"journal":{"name":"Iet Optoelectronics","volume":"16 3","pages":"116-123"},"PeriodicalIF":1.6,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/ote2.12062","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49054900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Low complexity deep learning algorithms for compensating atmospheric turbulence in the free space optical communication system 自由空间光通信系统中补偿大气湍流的低复杂度深度学习算法

IF 1.6 4区计算机科学

Iet Optoelectronics Pub Date : 2021-10-17 DOI: 10.1049/ote2.12060

Mohammad Ali Amirabadi, Mohammad Hossein Kahaei, S. Alireza Nezamalhosseni

{"title":"Low complexity deep learning algorithms for compensating atmospheric turbulence in the free space optical communication system","authors":"Mohammad Ali Amirabadi, Mohammad Hossein Kahaei, S. Alireza Nezamalhosseni","doi":"10.1049/ote2.12060","DOIUrl":"10.1049/ote2.12060","url":null,"abstract":"One of the main barriers of free space optical (FSO) communication systems is atmospheric turbulence. Various processing techniques at the transmitter, receiver, and transceiver sides are available for addressing this issue; however, they have either high complexity or low performance. Considering this problem, in this study, deep learning (DL) is deployed at the transmitter, receiver, and transceiver sides of an FSO system for constellation shaping, detection, and joint constellation-shaping detection, respectively. Furthermore, the proposed DL-based structures are deployed in an FSO-multi-input multi-output (MIMO) system. As the first investigation over DL for the FSO-MIMO system, different combining schemes including the maximum ratio combiner, equal gain combiner, and the selection combiner are considered. Considering a wide range of atmospheric turbulence, from the weak to the strong regime, the performance of the proposed structures are compared with that of the maximum likelihood (ML) detection. To the best of the authors' knowledge, the main contributions and novelties of this work include considering transmitter learning in the FSO system, designing low complexity DL structures for FSO system applications, and providing complexity analysis for the proposed DL algorithms. The results indicate that the proposed DL-based FSO systems achieve the optimum performance with lower complexity compared with the state-of-the-art conventional FSO systems. For instance, the proposed DL-based detector is almost 2, 3, and 7.5 times faster than the ML detector for modulation orders of 16, 64, and 256, respectively.","PeriodicalId":13408,"journal":{"name":"Iet Optoelectronics","volume":"16 3","pages":"93-105"},"PeriodicalIF":1.6,"publicationDate":"2021-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/ote2.12060","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44625395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10