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Progress in the research of directed thermal radiation
Zhiying Chen, Haotuo Liu, Xiaohu Wu, and Kaihua Zhang
Thermal radiation is a fundamental physical process that refers to the spontaneous emission of electromagnetic energy from objects with temperatures above absolute zero due to the thermal motion of particles. Most thermal radiators lack directionality, resulting in energy loss in unnecessary directions, which reduces tThermal radiation is a fundamental physical process that refers to the spontaneous emission of electromagnetic energy from objects with temperatures above absolute zero due to the thermal motion of particles. Most thermal radiators lack directionality, resulting in energy loss in unnecessary directions, which reduces the efficiency of many thermal devices and applications. In practical applications, thermal radiators are usually required to exhibit different thermal radiation capabilities in different directions, therefore, controlling the directionality of the thermal emission is crucial in efficient heat transfer. The study of directional thermal radiation is of great significance in thermal imaging and sensing, radiative cooling, infrared encryption, and energy utilization. The review first describes the difference between traditional and directional thermal radiation, as well as the potential value of the latter at the frontiers of science. Subsequently, based on the characteristics of thermal radiation, it systematically organizes the research progress of domestic and foreign scholars in directional thermal radiation in terms of both narrowband directional thermal radiation and broadband directional thermal radiation. Finally, future research trends in this field are envisioned, and major challenges are analyzed, aiming to provide theoretical guidance and practical insights for the further development of directional thermal radiation technology..
Opto-Electronic Engineering
- Publication Date: Sep. 25, 2024
- Vol. 51, Issue 9, 240128-1 (2024)
Article
Dual channel encrypted free-space optical communication system
Guoqing Wang, Rui Min, Xingquan Li, Haiping Zhang, Fang Zhao, Liyang Shao, and Ping Shen
A dual channel encrypted free-space optical communication system based on compressive sensing and tilted fiber grating is proposed. This approach not only greatly reduces the data acquisition volume, but also enhances the security of the system since the data transmitted in the free-space is encrypted. Besides, our proA dual channel encrypted free-space optical communication system based on compressive sensing and tilted fiber grating is proposed. This approach not only greatly reduces the data acquisition volume, but also enhances the security of the system since the data transmitted in the free-space is encrypted. Besides, our proposal adopts low-bandwidth and low-cost photodetectors and analog-to-digital convertors, decreasing the data acquisition volume and the cost of data transmission. Also, the approach utilizes the tilted fiber grating with a 45° tilted angle as the free-space light emitter, free-space light lateral diffraction device, and polarization-sensitive device, simultaneously. The utilization of 45° tilted fiber grating greatly enhances the systematic integration, reduces the volume of the system and improves the energy efficiency of the system. A demonstration shows that two 1 GHz and 3 GHz sinusoidal signals are employed for the 3.9 m free-space data transmission with data compression ratios of 16% and 8% achieved both in the time domain and frequency domain..
Opto-Electronic Engineering
- Publication Date: Sep. 25, 2024
- Vol. 51, Issue 9, 240106-1 (2024)
Quadrupl-stream input-guided feature complementary visible-infrared person re-identification
Bin Ge, Nuo Xu, Chenxing Xia, and Haijun Zheng
Current visible-infrared person re-identification research focuses on extracting modal shared saliency features through the attention mechanism to minimize modal differences. However, these methods only focus on the most salient features of pedestrians, and cannot make full use of modal information. To solve this problCurrent visible-infrared person re-identification research focuses on extracting modal shared saliency features through the attention mechanism to minimize modal differences. However, these methods only focus on the most salient features of pedestrians, and cannot make full use of modal information. To solve this problem, a quadrupl-stream input-guided feature complementary network (QFCNet) is proposed in this paper. Firstly, a quadrupl-stream feature extraction and fusion module is designed in the mode-specific feature extraction stage. By adding two data enhancement inputs, the color differences between modalities are alleviated, the semantic information of the modalities is enriched and the multi-dimensional feature fusion is further promoted. Secondly, a sub-salient feature complementation module is designed to supplement the pedestrian detail information ignored by the attention mechanism in the global feature through the inversion operation, to strengthen the pedestrian discriminative features. The experimental results on two public datasets SYSU-MM01 and RegDB show the superiority of this method. In the full search mode of SYSU-MM01, the rank-1 and mAP values reach 76.12% and 71.51%, respectively..
Opto-Electronic Engineering
- Publication Date: Sep. 25, 2024
- Vol. 51, Issue 9, 240119-1 (2024)
No-reference light field image quality assessment based on joint spatial-angular information
Bin Wang, Yongqiang Bai, Zhongjie Zhu, Mei Yu, and Gangyi Jiang
Light field images provide users with a more comprehensive and realistic visual experience by recording information from multiple viewpoints. However, distortions introduced during the acquisition and visualization process can severely impact their visual quality. Therefore, effectively evaluating the quality of light Light field images provide users with a more comprehensive and realistic visual experience by recording information from multiple viewpoints. However, distortions introduced during the acquisition and visualization process can severely impact their visual quality. Therefore, effectively evaluating the quality of light field images is a significant challenge. This paper proposes a no-reference light field image quality assessment method based on deep learning, combining spatial-angular features and epipolar plane information. Firstly, a spatial-angular feature extraction network is constructed to capture multi-scale semantic information through multi-level connections, and a multi-scale fusion approach is employed to achieve effective dual-feature extraction. Secondly, a bidirectional epipolar plane image feature learning network is proposed to effectively assess the angular consistency of light field images. Finally, image quality scores are output through cross-feature fusion and linear regression. Comparative experimental results on three common datasets indicate that the proposed method significantly outperforms classical 2D image and light field image quality assessment methods, with a higher consistency with subjective evaluation results..
Opto-Electronic Engineering
- Publication Date: Sep. 25, 2024
- Vol. 51, Issue 9, 240139-1 (2024)
Dual low-light images combining color correction and structural information enhance
Shanling Lin, Yan Chen, Xue Zhang, Zhixian Lin, Jianpu Lin, Shanhong Lv, and Tailiang Guo
To enhance image quality in low-light conditions, an unsupervised dual-path low-light image enhancement algorithm is proposed, integrating color correction and structural information. The algorithm utilizes a generative adversarial network (GAN) with a generator that employs a dual-branch architecture to concurrently hTo enhance image quality in low-light conditions, an unsupervised dual-path low-light image enhancement algorithm is proposed, integrating color correction and structural information. The algorithm utilizes a generative adversarial network (GAN) with a generator that employs a dual-branch architecture to concurrently handle color and structural details, resulting in natural color restoration and clear texture details. A spatial-discriminative block (SDB) is introduced in the discriminator to improve its judgment capability, leading to more realistic image generation. An illumination-guided color correction block (IGCB) uses illumination features to mitigate noise and artifacts in low-light environments. The selective kernel channel fusion (SKCF) and convolution attention block (CAB) modules enhance the semantic and local details of the image. Experimental results show that the algorithm outperforms classical methods on the LOL and LSRW datasets, achieving PSNR and SSIM scores of 19.89 and 0.672, respectively, on the LOLv1 dataset, and 20.08 and 0.693 on the LOLv2 dataset. Practical applications confirm its effectiveness in restoring brightness, contrast, and color in low-light images..
Opto-Electronic Engineering
- Publication Date: Sep. 25, 2024
- Vol. 51, Issue 9, 240142-1 (2024)
Demodulation method for GaAs optical fiber temperature sensing based on reference filter and cross-correlation algorithm
Yang Bi, Zhifu Xiong, Jiawen Li, Tianyu Yang, Huanhuan Liu, Huiming Wan, and Yuming Dong
This paper presents a new demodulation approach for optical fiber temperature sensors based on GaAs, leveraging reference filtering and a cross-correlation algorithm. It preprocesses the data through double Gaussian filtering for smoothing and implements an enhanced cross-correlation algorithm adopting a long-pass filtThis paper presents a new demodulation approach for optical fiber temperature sensors based on GaAs, leveraging reference filtering and a cross-correlation algorithm. It preprocesses the data through double Gaussian filtering for smoothing and implements an enhanced cross-correlation algorithm adopting a long-pass filter (LPF) waveform as the reference signal to demodulate the GaAs optical fiber temperature sensor. Using the correlated data from cross-correlation operations, it applies a multiple polynomial fitting strategy to further augment the precision of the cross-correlation algorithm’s demodulation. Across a temperature sensing range of ?30 to 250 ℃, the wavelength demodulation error of this method can reach ±0.0016 nm, and the temperature demodulation accuracy is ±0.388 ℃. Relative to the prevailing normalized optical intensity demodulation method, the cross-correlation algorithm employing an LPF waveform as the reference demonstrates a 2.64-fold increase in noise immunity and a 2.08-fold improvement over cross-correlation algorithms without the LPF reference waveform..
Opto-Electronic Engineering
- Publication Date: Sep. 25, 2024
- Vol. 51, Issue 9, 240143-1 (2024)
Adaptive foreground focusing for target detection in UAV aerial images
Zhenjiu Xiao, Zhengwei Wu, Jiehao Zhang, and Haicheng Qu
To address the issues of missed and false detections caused by significant scale differences of foreground targets, uneven sample spatial distribution, and high background redundancy in UAV aerial images, an adaptive foreground-focused UAV aerial image target detection algorithm is proposed. A panoramic feature refinemTo address the issues of missed and false detections caused by significant scale differences of foreground targets, uneven sample spatial distribution, and high background redundancy in UAV aerial images, an adaptive foreground-focused UAV aerial image target detection algorithm is proposed. A panoramic feature refinement classification layer is constructed to enhance the algorithm's focusing capability and improve the representation quality of foreground sample features through the re-parameterization spatial pixel variance method and shuffling operation. An adaptive dual-dimensional feature sampling unit is designed using a separate-learn-merge strategy to strengthen the algorithm's ability to extract foreground focus features and retain background detail information, thereby improving false detection situations and accelerating inference speed. A multi-path information integration module is constructed by combining a multi-branch structure and a broadcast self-attention mechanism to solve the ambiguity mapping problem caused by downsampling, optimize feature interaction and integration, enhance the algorithm's ability to recognize and locate multi-scale targets, and reduce model computational load. An adaptive foreground-focused detection head is introduced, which employs a dynamic focusing mechanism to enhance foreground target detection accuracy and suppress background interference. Experiments on the public datasets VisDrone2019 and VisDrone2021 show that the proposed method achieves mAP@0.5 values of 45.1% and 43.1%, respectively, improving by 6.6% and 5.7% compared to the baseline model, and outperforming other comparison algorithms. These results demonstrate that the proposed algorithm significantly improves detection accuracy and possesses good generalizability and real-time performance..
Opto-Electronic Engineering
- Publication Date: Sep. 25, 2024
- Vol. 51, Issue 9, 240149-1 (2024)