Journals >Optoelectronics Letters
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2025
Volume: 21 Issue 4
9 Article(s)
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A highly-integrated fiber fluid sensing system of metal ion concentrations with resistance to temperature crosstalk
Junqi GUO, Qianwen XU, Binwei GUO, Andrei KULIKOV... and Jiwen CUI|Show fewer author(s)
To address the temperature cross-talk issue in detecting heavy metal ions in natural waters, a highly-integrated and fully fiber-optic metal ion sensing system capable of temperature-concentration decoupling measurement has been designed. This system integrates a fluidic detection structure assisted by side-polished fiTo address the temperature cross-talk issue in detecting heavy metal ions in natural waters, a highly-integrated and fully fiber-optic metal ion sensing system capable of temperature-concentration decoupling measurement has been designed. This system integrates a fluidic detection structure assisted by side-polished fibers (SPFs) with a Sagnac interferometer. By selecting common refractive index ranges of contaminated water sources and common environmental temperature ranges, numerical simulations were conducted to analyze the sensing characteristics of the photonic bandgap boundary and interference spectrum wavelength in relation to these two parameters, and finally, a temperature and refractive index decoupling model was obtained. Results show that this system successfully demodulates the temperature parameter in solution refractive index sensing, exhibiting a concentration sensitivity of −355.96 nm∙mL/mol and a temperature interference of −2.03 nm/°C..
Optoelectronics Letters
- Publication Date: Feb. 28, 2025
- Vol. 21, Issue 4, 193 (2025)
Fiber optic high temperature sensor with weak strain sensitivity based on Mach-Zehnder interferometric structure
Ming LIU, Chengju MA, Yixin ZHANG, Qianzhen LIU... and Jirui WU|Show fewer author(s)
We proposed a fiber optic high temperature sensor based on the Mach-Zehnder interference (MZI) structure, which is composed of two lengths of multi-mode fibers (MMFs), a length of few-mode fiber (FMF) and two sections of single-mode fibers (SMFs). Firstly, the two sections of MMFs were spliced with two sections of SMFsWe proposed a fiber optic high temperature sensor based on the Mach-Zehnder interference (MZI) structure, which is composed of two lengths of multi-mode fibers (MMFs), a length of few-mode fiber (FMF) and two sections of single-mode fibers (SMFs). Firstly, the two sections of MMFs were spliced with two sections of SMFs. Then, the MMFs were fused to two ends of FMF to form a symmetrically structured fiber-optic MZI structure. In this structure, the MMF served as the optical mode field coupling element, and the cladding and core of the FMF are the interference arm and the reference arm of the MZI structure, respectively. We investigated the sensor’s response characteristics of the temperature and strain. The experimental results indicate that the sensor is sensitive to temperature variation, and the temperature response sensitivity is up to 61.4 pm/℃ in the range of 40—250 ℃, while the sensor has weak strain sensitivity, its strain sensitivity is only −0.72 pm/με in the strain range of 0—1 400 με. Moreover, the sensor has good stability and repeatability. In brief, the proposed fiber optic high temperature sensor has good properties, such as high sensitivity, compact structure, good stability and repeatability, which can be used for monitoring the temperature of submerged oil electric pump units under oil wells..
Optoelectronics Letters
- Publication Date: Feb. 28, 2025
- Vol. 21, Issue 4, 199 (2025)
Modeling and simulation of a reconfigurable multifunctional optical sensor
Shaher DWIK, and Gurusamy SASIKALA
Position sensitive device (PSD) sensor is a vital optical element that is mainly used in tracking systems for visible light communication (VLC). Recently, a new reconfigurable PSD architecture emerged. The proposed architecture makes the PSD perform more functions by modifying its architecture. As the PSD is mainly forPosition sensitive device (PSD) sensor is a vital optical element that is mainly used in tracking systems for visible light communication (VLC). Recently, a new reconfigurable PSD architecture emerged. The proposed architecture makes the PSD perform more functions by modifying its architecture. As the PSD is mainly formed of an array of photodiodes. The primary concept involves employing transistors to alternate between the operating modes of the photodiodes (photoconductive and photovoltaic). Additionally, alternating among output pins can be done based on the required function. This paper presents the mathematical modeling and simulation of a reconfigurable-multifunctional optical sensor which can perform energy harvesting and data acquisition, as well as positioning, which is not available in the traditional PSDs. Simulation using the MATLAB software tool was achieved to demonstrate the modeling. The simulation results confirmed the validity of the mathematical modeling and proved that the modified sensor architecture, as depicted by the equations, accurately describes its behavior. The proposed sensor is expected to extend the battery’s lifecycle, reduce its physical size, and increase the integration and functionality of the system. The presented sensor might be used in free space optical (FSO) communication like cube satellites or even in underwater wireless optical communication (UWOC)..
Optoelectronics Letters
- Publication Date: Feb. 28, 2025
- Vol. 21, Issue 4, 205 (2025)
Design of improved error-rate sliding window decoder for SC-LDPC codes: reliable termination and channel value reuse
Xishan JIA, Jining LI, Yuan YAO, Yifan WANG... and Degang XU|Show fewer author(s)
In this paper, an improved error-rate sliding window decoder is proposed for spatially coupled low-density parity-check (SC-LDPC) codes. For the conventional sliding window decoder, the message retention mechanism causes unreliable messages along the edges of belief propagation (BP) decoding in the current window to beIn this paper, an improved error-rate sliding window decoder is proposed for spatially coupled low-density parity-check (SC-LDPC) codes. For the conventional sliding window decoder, the message retention mechanism causes unreliable messages along the edges of belief propagation (BP) decoding in the current window to be kept for subsequent window decoding. To improve the reliability of the retained messages during the window transition, a reliable termination method is embedded, where the retained messages undergo more reliable parity checks. Additionally, decoding failure is unavoidable and even causes error propagation when the number of errors exceeds the error-correcting capability of the window. To mitigate this problem, a channel value reuse mechanism is designed, where the received channel values are utilized to reinitialize the window. Furthermore, considering the complexity and performance of decoding, a feasible sliding optimized window decoding (SOWD) scheme is introduced. Finally, simulation results confirm the superior performance of the proposed SOWD scheme in both the waterfall and error floor regions. This work has great potential in the applications of wireless optical communication and fiber optic communication..
Optoelectronics Letters
- Publication Date: Feb. 28, 2025
- Vol. 21, Issue 4, 212 (2025)
Infrared small target detection based on density peaks searching and weighted multi-feature local difference
Bin JI, Pengxiang FAN, Mengli WANG, Yang LIU, and Jiafeng XU
To address the issues of unknown target size, blurred edges, background interference and low contrast in infrared small target detection, this paper proposes a method based on density peaks searching and weighted multi-feature local difference. Firstly, an improved high-boost filter is used for preprocessing to eliminaTo address the issues of unknown target size, blurred edges, background interference and low contrast in infrared small target detection, this paper proposes a method based on density peaks searching and weighted multi-feature local difference. Firstly, an improved high-boost filter is used for preprocessing to eliminate background clutter and high-brightness interference, thereby increasing the probability of capturing real targets in the density peak search. Secondly, a triple-layer window is used to extract features from the area surrounding candidate targets, addressing the uncertainty of small target sizes. By calculating multi-feature local differences between the triple-layer windows, the problems of blurred target edges and low contrast are resolved. To balance the contribution of different features, intra-class distance is used to calculate weights, achieving weighted fusion of multi-feature local differences to obtain the weighted multi-feature local differences of candidate targets. The real targets are then extracted using the interquartile range. Experiments on datasets such as SIRST and IRSTD-1K show that the proposed method is suitable for various complex types and demonstrates good robustness and detection performance..
Optoelectronics Letters
- Publication Date: Feb. 28, 2025
- Vol. 21, Issue 4, 218 (2025)
Multi-scale feature fusion optical remote sensing target detection method
Liang BAI, Xuewen DING, Ying LIU, and Limei CHANG
An improved model based on you only look once version 8 (YOLOv8) is proposed to solve the problem of low detection accuracy due to the diversity of object sizes in optical remote sensing images. Firstly, the feature pyramid network (FPN) structure of the original YOLOv8 mode is replaced by the generalized-FPN (GFPN) stAn improved model based on you only look once version 8 (YOLOv8) is proposed to solve the problem of low detection accuracy due to the diversity of object sizes in optical remote sensing images. Firstly, the feature pyramid network (FPN) structure of the original YOLOv8 mode is replaced by the generalized-FPN (GFPN) structure in GiraffeDet to realize the "cross-layer" and "cross-scale" adaptive feature fusion, to enrich the semantic information and spatial information on the feature map to improve the target detection ability of the model. Secondly, a pyramid-pool module of multi atrous spatial pyramid pooling (MASPP) is designed by using the idea of atrous convolution and feature pyramid structure to extract multi-scale features, so as to improve the processing ability of the model for multi-scale objects. The experimental results show that the detection accuracy of the improved YOLOv8 model on DIOR dataset is 92% and mean average precision (mAP) is 87.9%, respectively 3.5% and 1.7% higher than those of the original model. It is proved the detection and classification ability of the proposed model on multi-dimensional optical remote sensing target has been improved..
Optoelectronics Letters
- Publication Date: Feb. 28, 2025
- Vol. 21, Issue 4, 226 (2025)
Variety classification and identification of maize seeds based on hyperspectral imaging method
Hang XUE, Xiping XU, and Xiang MENG
In this study, eight different varieties of maize seeds were used as the research objects. Conduct 81 types of combined preprocessing on the original spectra. Through comparison, Savitzky-Golay (SG)-multivariate scattering correction (MSC)-maximum-minimum normalization (MN) was identified as the optimal preprocessing tIn this study, eight different varieties of maize seeds were used as the research objects. Conduct 81 types of combined preprocessing on the original spectra. Through comparison, Savitzky-Golay (SG)-multivariate scattering correction (MSC)-maximum-minimum normalization (MN) was identified as the optimal preprocessing technique. The competitive adaptive reweighted sampling (CARS), successive projections algorithm (SPA), and their combined methods were employed to extract feature wavelengths. Classification models based on back propagation (BP), support vector machine (SVM), random forest (RF), and partial least squares (PLS) were established using full-band data and feature wavelengths. Among all models, the (CARS-SPA)-BP model achieved the highest accuracy rate of 98.44%. This study offers novel insights and methodologies for the rapid and accurate identification of corn seeds as well as other crop seeds..
Optoelectronics Letters
- Publication Date: Feb. 28, 2025
- Vol. 21, Issue 4, 234 (2025)
Rendered image denoising method with filtering guided by lighting information
Minghui MA, Xiaojuan HU, Ripei ZHANG, Chunyi CHEN, and Haiyang YU
The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method. However, the existing denoising algorithms have limited denoising performance under complex lighting conditions and are easy to lose detailed information. So we propose a rendered image denoising method with filterThe visual noise of each light intensity area is different when the image is drawn by Monte Carlo method. However, the existing denoising algorithms have limited denoising performance under complex lighting conditions and are easy to lose detailed information. So we propose a rendered image denoising method with filtering guided by lighting information. First, we design an image segmentation algorithm based on lighting information to segment the image into different illumination areas. Then, we establish the parameter prediction model guided by lighting information for filtering (PGLF) to predict the filtering parameters of different illumination areas. For different illumination areas, we use these filtering parameters to construct area filters, and the filters are guided by the lighting information to perform sub-area filtering. Finally, the filtering results are fused with auxiliary features to output denoised images for improving the overall denoising effect of the image. Under the physically based rendering tool (PBRT) scene and Tungsten dataset, the experimental results show that compared with other guided filtering denoising methods, our method improves the peak signal-to-noise ratio (PSNR) metrics by 4.216 4 dB on average and the structural similarity index (SSIM) metrics by 7.8% on average. This shows that our method can better reduce the noise in complex lighting scenes and improve the image quality..
Optoelectronics Letters
- Publication Date: Feb. 28, 2025
- Vol. 21, Issue 4, 242 (2025)
YOLO-based lightweight traffic sign detection algorithm and mobile deployment
Yaqin WU, Tao ZHANG, Jianjun NIU, Yan CHANG, and Ganjun LIU
This paper proposes a lightweight traffic sign detection system based on you only look once (YOLO). Firstly, the classification to fusion (C2f) structure is integrated into the backbone network, employing deformable convolution and bi-directional feature pyramid network (BiFPN)~~Concat to improve the adaptability of thThis paper proposes a lightweight traffic sign detection system based on you only look once (YOLO). Firstly, the classification to fusion (C2f) structure is integrated into the backbone network, employing deformable convolution and bi-directional feature pyramid network (BiFPN)_Concat to improve the adaptability of the network. Secondly, the simple attention module (SimAm) is embedded to prioritize key features and reduce the complexity of the model after the C2f layer at the end of the backbone network. Next, the focal efficient intersection over union (EIoU) is introduced to adjust the weights of challenging samples. Finally, we accomplish the design and deployment for the mobile app. The results demonstrate improvements, with the F1 score of 0.898 7, mean average precision (mAP)@0.5 of 98.8%, mAP@0.5: 0.95 of 75.6%, and the detection speed of 50 frames per second (FPS)..
Optoelectronics Letters
- Publication Date: Feb. 28, 2025
- Vol. 21, Issue 4, 249 (2025)
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