Atmospheric turbulence is a major challenge in long-range imaging of ground-based telescopes, especially in the surveillance of space targets, whose observation distance is usually more than 100 km. In this case, space targets are extremely small in images, occupying less than 0.12% of the total image area, and suffer from severe blur and distortion. Consequently, the accuracy of object detection by both conventional and deep-learning-based methods is significantly hampered. Therefore, this paper proposes an effective framework for detecting space target through atmospheric turbulence. The framework incorporates a shallow deblurring module, a transformer-based feature extractor, and a small region proposal network. The training data comprises simulated degraded images of space target images against celestial backgrounds, as well as a selection of images from the Dotav2 dataset. Testing results show that the proposed framework outperforms the general framework, achieving a mean Average Precision (mAP) improvement of over 20%.
{"title":"Effective framework for space target detection through atmospheric turbulence","authors":"Yiming Chen, Jing Wang, Zhehan Song, Haoying Li, Ziran Zhang, Qi Li, Zhi-hai Xu, H. Feng, Yue-ting Chen","doi":"10.1117/12.3005214","DOIUrl":"https://doi.org/10.1117/12.3005214","url":null,"abstract":"Atmospheric turbulence is a major challenge in long-range imaging of ground-based telescopes, especially in the surveillance of space targets, whose observation distance is usually more than 100 km. In this case, space targets are extremely small in images, occupying less than 0.12% of the total image area, and suffer from severe blur and distortion. Consequently, the accuracy of object detection by both conventional and deep-learning-based methods is significantly hampered. Therefore, this paper proposes an effective framework for detecting space target through atmospheric turbulence. The framework incorporates a shallow deblurring module, a transformer-based feature extractor, and a small region proposal network. The training data comprises simulated degraded images of space target images against celestial backgrounds, as well as a selection of images from the Dotav2 dataset. Testing results show that the proposed framework outperforms the general framework, achieving a mean Average Precision (mAP) improvement of over 20%.","PeriodicalId":502341,"journal":{"name":"Applied Optics and Photonics China","volume":"88 ","pages":"1296205 - 1296205-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139175838","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}
Haoyu Zhang, Yuying Mei, Yadi Chen, Zhe Xie, Bing Lei
A pulse position modulation (PPM) algorithm is designed and implemented to counter atmospheric turbulence interference in free-space optical (FSO) communication. A homemade turbulence simulation device based on thermal wind has been constructed to simulated a atmospheric turbulence channel, and it has been utilized to check the performance of the FSO communication system in atmospheric turbulence conditions. Both the signal modulation schemes of 4-ary pulse position modulation (4-PPM) and non-return-to-zero (NRZ) on-off keying (OOK) are implemented and compared in the system, and their corresponding modulation and demodulation algorithms have been realized using the field-programmable gate arrays (FPGA). To verify the effectiveness and practical performance of the PPM algorithm, extensive experiments have been carried out on the FSO communication system under laboratory- simulated atmospheric turbulence conditions, and the bit error rates (BER) of the PPM and OOK modulation schemes have been obtained and compared. The experimental results in the simulating atmospheric turbulence channel show that the PPM modulation system designed in this study yields a lower BER than the OOK modulation system under different turbulence intensities. Furthermore, as the turbulence intensity increases, the BER’s improvement of the PPM modulation system becomes more remarkable. The research results indicate the FSO communication system with PPM modulation possesses superior performance in an atmospheric turbulence channel.
设计并实现了一种脉冲位置调制（PPM）算法，以对抗自由空间光学（FSO）通信中的大气湍流干扰。利用自制的基于热风的湍流模拟装置模拟了大气湍流信道，并利用它检验了 FSO 通信系统在大气湍流条件下的性能。系统中实现并比较了四元脉冲位置调制（4-PPM）和非归零（NRZ）开关键控（OOK）两种信号调制方案，并使用现场可编程门阵列（FPGA）实现了相应的调制和解调算法。为了验证 PPM 算法的有效性和实用性能，我们在实验室模拟的大气湍流条件下对 FSO 通信系统进行了大量实验，获得并比较了 PPM 和 OOK 调制方案的误码率（BER）。模拟大气湍流信道的实验结果表明，在不同的湍流强度下，本研究设计的 PPM 调制系统比 OOK 调制系统产生更低的误码率。此外，随着湍流强度的增加，PPM 调制系统的误码率改善更为显著。研究结果表明，采用 PPM 调制的 FSO 通信系统在大气湍流信道中性能优越。
{"title":"Design and implementation of PPM modulation and demodulation algorithm in atmospheric turbulence channel","authors":"Haoyu Zhang, Yuying Mei, Yadi Chen, Zhe Xie, Bing Lei","doi":"10.1117/12.3007672","DOIUrl":"https://doi.org/10.1117/12.3007672","url":null,"abstract":"A pulse position modulation (PPM) algorithm is designed and implemented to counter atmospheric turbulence interference in free-space optical (FSO) communication. A homemade turbulence simulation device based on thermal wind has been constructed to simulated a atmospheric turbulence channel, and it has been utilized to check the performance of the FSO communication system in atmospheric turbulence conditions. Both the signal modulation schemes of 4-ary pulse position modulation (4-PPM) and non-return-to-zero (NRZ) on-off keying (OOK) are implemented and compared in the system, and their corresponding modulation and demodulation algorithms have been realized using the field-programmable gate arrays (FPGA). To verify the effectiveness and practical performance of the PPM algorithm, extensive experiments have been carried out on the FSO communication system under laboratory- simulated atmospheric turbulence conditions, and the bit error rates (BER) of the PPM and OOK modulation schemes have been obtained and compared. The experimental results in the simulating atmospheric turbulence channel show that the PPM modulation system designed in this study yields a lower BER than the OOK modulation system under different turbulence intensities. Furthermore, as the turbulence intensity increases, the BER’s improvement of the PPM modulation system becomes more remarkable. The research results indicate the FSO communication system with PPM modulation possesses superior performance in an atmospheric turbulence channel.","PeriodicalId":502341,"journal":{"name":"Applied Optics and Photonics China","volume":"13 10","pages":"129590V - 129590V-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139175948","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}
Using the image square scanning mechanism, a large field of view infrared optical system is designed. The field of view of the optical system is increased by 16 times compared with the theoretical value. It has the characteristics of small size, light weight and simple structure. The working spectral region is 8~12μm, the focal length is 90mm, the scanning field of view is ±24°, and the instantaneous field of view is 3°. The system has image quality close to the diffraction limit in the full field of view, and can be applied to photoelectric reconnaissance systems with miniaturization requirements to solve the problems of future high-speed and miniaturization.
{"title":"Infrared optical design with large FOV based on image space scanning","authors":"Ming Li","doi":"10.1117/12.3005469","DOIUrl":"https://doi.org/10.1117/12.3005469","url":null,"abstract":"Using the image square scanning mechanism, a large field of view infrared optical system is designed. The field of view of the optical system is increased by 16 times compared with the theoretical value. It has the characteristics of small size, light weight and simple structure. The working spectral region is 8~12μm, the focal length is 90mm, the scanning field of view is ±24°, and the instantaneous field of view is 3°. The system has image quality close to the diffraction limit in the full field of view, and can be applied to photoelectric reconnaissance systems with miniaturization requirements to solve the problems of future high-speed and miniaturization.","PeriodicalId":502341,"journal":{"name":"Applied Optics and Photonics China","volume":"64 2","pages":"1296008 - 1296008-7"},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139173780","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}
Aiming at a series of problems caused by the position sensor required by the salient pole permanent magnet synchronous motor (IPMSM) control system, a high-frequency square wave injection sensorless control algorithm suitable for IPMSM low-speed control system is realized in this paper. Compared with other sensorless control algorithms, its advantages are that it avoids the system delay caused by the filter by injecting high-frequency square wave signal, and has good stability and robustness at low speed. The feasibility and effectiveness of this method are verified by simulation. At the same time, it shows that the high-frequency square wave injection method has good accuracy of rotor position estimation, and can ensure the good stability and dynamic performance of the whole drive system. Through the simulation results, better injection voltage amplitude is selected to reduce the electromagnetic interference and electromagnetic noise caused by high-frequency square wave injection signal.
{"title":"IPMSM sensorless control technology based on high frequency square wave injection method","authors":"Zhiliang Yu, Yu Zhang, Yu Feng, Yuan Wang, Chengmiao Xu","doi":"10.1117/12.3000610","DOIUrl":"https://doi.org/10.1117/12.3000610","url":null,"abstract":"Aiming at a series of problems caused by the position sensor required by the salient pole permanent magnet synchronous motor (IPMSM) control system, a high-frequency square wave injection sensorless control algorithm suitable for IPMSM low-speed control system is realized in this paper. Compared with other sensorless control algorithms, its advantages are that it avoids the system delay caused by the filter by injecting high-frequency square wave signal, and has good stability and robustness at low speed. The feasibility and effectiveness of this method are verified by simulation. At the same time, it shows that the high-frequency square wave injection method has good accuracy of rotor position estimation, and can ensure the good stability and dynamic performance of the whole drive system. Through the simulation results, better injection voltage amplitude is selected to reduce the electromagnetic interference and electromagnetic noise caused by high-frequency square wave injection signal.","PeriodicalId":502341,"journal":{"name":"Applied Optics and Photonics China","volume":"81 ","pages":"1296505 - 1296505-7"},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139174958","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}
High-resolution three-dimensional brain image reconstruction is crucial for understanding the brain. Light sheet microscopy combined with tissue clearing imaging plays a pivotal role in analyzing the micro-level structure of mammalian brains. However, the complex multi-level stitching process poses challenges such as non-overlapping areas, surface deformation, and tissue loss, resulting in incomplete or discontinuous tissue structures at the junctions. These issues not only impact the precision of the atlas but also complicate subsequent analyses like cell counting and neuron tracing. To address these issues, we propose a rapid deep learning-based image inpainting approach for accurate neuron reconstruction and analysis. Our approach involves initially employing conventional registration algorithms to preliminarily stitch brain sections together, followed by utilizing a neural network to predict and restore missing tissue with a thickness exceeding 10 µm. This process enhances the structural continuity and integrity between adjacent brain slices. Compared to the original 3D U-Net and ResNet models, our approach performs better and has a processing speed that is five times faster than the original 3D U-Net. Moreover, our method enables more accurate cell counting by repairing incomplete cell bodies, leading to an average improvement of 37.37% in the number of cell bodies accurately counted near the slice junction. By integrating this novel 3D image inpainting network into brain reconstruction processes, our research opens new avenues for a more detailed and accurate investigation of neural circuitry and neurological disorders.
{"title":"Fast and lightweight network improves serial brain section stitching","authors":"Lianchao Wang, Jiajia Chen, W. Gong, Ke Si","doi":"10.1117/12.3005396","DOIUrl":"https://doi.org/10.1117/12.3005396","url":null,"abstract":"High-resolution three-dimensional brain image reconstruction is crucial for understanding the brain. Light sheet microscopy combined with tissue clearing imaging plays a pivotal role in analyzing the micro-level structure of mammalian brains. However, the complex multi-level stitching process poses challenges such as non-overlapping areas, surface deformation, and tissue loss, resulting in incomplete or discontinuous tissue structures at the junctions. These issues not only impact the precision of the atlas but also complicate subsequent analyses like cell counting and neuron tracing. To address these issues, we propose a rapid deep learning-based image inpainting approach for accurate neuron reconstruction and analysis. Our approach involves initially employing conventional registration algorithms to preliminarily stitch brain sections together, followed by utilizing a neural network to predict and restore missing tissue with a thickness exceeding 10 µm. This process enhances the structural continuity and integrity between adjacent brain slices. Compared to the original 3D U-Net and ResNet models, our approach performs better and has a processing speed that is five times faster than the original 3D U-Net. Moreover, our method enables more accurate cell counting by repairing incomplete cell bodies, leading to an average improvement of 37.37% in the number of cell bodies accurately counted near the slice junction. By integrating this novel 3D image inpainting network into brain reconstruction processes, our research opens new avenues for a more detailed and accurate investigation of neural circuitry and neurological disorders.","PeriodicalId":502341,"journal":{"name":"Applied Optics and Photonics China","volume":"19 6","pages":"129631V - 129631V-9"},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139175357","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}
Ting Ji, Yu Liu, Yawei Wang, Zhidong Liu, Lijun Zhou, Fei Liu, Song Li, Yixuan Kang, Qinglin Zhao, Kai Shi, Yuxin Gao, Xuetao Jia, Heng Lu
In order to improve the anti-interference and tracking performance of photoelectric stabilized platform, a sliding mode controller based on reaching law was designed. Since the differential signal of the input was used in the sliding mode controller, if the noise was added in the input signal, its differential signal will amplify the noise, thus affecting the actual effect of the controller. To solve this problem, a method combining nonlinear Tracking Differentiator (TD) with sliding mode controller was proposed ,then the experimental system was built, and the results of the new controller and the traditional PID controller were compared. It is proved that the method this article presented can improve the anti-interference performance of the system by 66.7%, and also can increase the track precision of the input signal by 48.2%.
{"title":"Sliding mode control of photoelectric stabilized platform based on nonlinear tracking differentiator","authors":"Ting Ji, Yu Liu, Yawei Wang, Zhidong Liu, Lijun Zhou, Fei Liu, Song Li, Yixuan Kang, Qinglin Zhao, Kai Shi, Yuxin Gao, Xuetao Jia, Heng Lu","doi":"10.1117/12.3000057","DOIUrl":"https://doi.org/10.1117/12.3000057","url":null,"abstract":"In order to improve the anti-interference and tracking performance of photoelectric stabilized platform, a sliding mode controller based on reaching law was designed. Since the differential signal of the input was used in the sliding mode controller, if the noise was added in the input signal, its differential signal will amplify the noise, thus affecting the actual effect of the controller. To solve this problem, a method combining nonlinear Tracking Differentiator (TD) with sliding mode controller was proposed ,then the experimental system was built, and the results of the new controller and the traditional PID controller were compared. It is proved that the method this article presented can improve the anti-interference performance of the system by 66.7%, and also can increase the track precision of the input signal by 48.2%.","PeriodicalId":502341,"journal":{"name":"Applied Optics and Photonics China","volume":"81 ","pages":"1296306 - 1296306-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139175505","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}
The dual-frequency coherent lidar (DFCL) has advantages of anti-interference, stability, and can obtain low Doppler frequency shift in high-speed dynamic target detection. A performance evaluation model of DFCL is established for remote Gaussian rough object detection. The detection ability is closely related to laser echo characteristics, especially the intensity and coherence. The laser beam radius on the far field increases with the decay of the emitted laser pulse coherence, and the atmospheric turbulence reduces the coherence further. The intensity utilization factor is defined and calculated. The decoherence effects of rough surfaces are calculated via the complex coherence degree under typical roughness parameters and laser wavelength. Moreover, the Doppler frequency shift is proportional to dual-frequency difference ∆f, but the signal-to-noise ratio (SNR) decreases with larger ∆f duo to the coherence reduction of dual-frequency laser, and the optimal dual-frequency difference ∆fm selection criteria is determined for practical applications; and the system efficiency reduction factor are calculated and compared under typical detection parameters. Finally, the combined effects of laser source coherence, atmospheric turbulence, optical parameters and ∆f on the SNR improvements are analyzed considering dual-frequency and single frequency lidar systems. This research is of significance to reveal the dual-frequency coherent detection process and the optimization method of coherent lidar systems.
{"title":"Performance analysis of dual-frequency coherent lidar for rough target detection in turbulent atmosphere","authors":"Xiao Dong, Huizhen Bai, Shilong Xu","doi":"10.1117/12.3007941","DOIUrl":"https://doi.org/10.1117/12.3007941","url":null,"abstract":"The dual-frequency coherent lidar (DFCL) has advantages of anti-interference, stability, and can obtain low Doppler frequency shift in high-speed dynamic target detection. A performance evaluation model of DFCL is established for remote Gaussian rough object detection. The detection ability is closely related to laser echo characteristics, especially the intensity and coherence. The laser beam radius on the far field increases with the decay of the emitted laser pulse coherence, and the atmospheric turbulence reduces the coherence further. The intensity utilization factor is defined and calculated. The decoherence effects of rough surfaces are calculated via the complex coherence degree under typical roughness parameters and laser wavelength. Moreover, the Doppler frequency shift is proportional to dual-frequency difference ∆f, but the signal-to-noise ratio (SNR) decreases with larger ∆f duo to the coherence reduction of dual-frequency laser, and the optimal dual-frequency difference ∆fm selection criteria is determined for practical applications; and the system efficiency reduction factor are calculated and compared under typical detection parameters. Finally, the combined effects of laser source coherence, atmospheric turbulence, optical parameters and ∆f on the SNR improvements are analyzed considering dual-frequency and single frequency lidar systems. This research is of significance to reveal the dual-frequency coherent detection process and the optimization method of coherent lidar systems.","PeriodicalId":502341,"journal":{"name":"Applied Optics and Photonics China","volume":"47 2","pages":"1295914 - 1295914-9"},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139175560","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}
Deep reinforcement learning (DRL) has been introduced in routing, modulation and spectrum assignment (RMSA) of the elastic optical networks. Since the DRL agent’s learning is based on the state it observes and the reward it receives, key information should be embedded in the state and the reward. In previous studies, the observed and feedback information is limited. In this paper, we propose a busyness level-based DRL method for the RMSA of the elastic optical networks. Since the busyness of the links or transmission paths highly affects the performance, we believe the busyness information should be perceived by the agent to learn a good RMSA policy. Specifically, we define two indicators to quantify busyness level, and then combine these two indicators into the design of reward and state. Simulation results show that our approach works better than the case that busyness is not
{"title":"Busyness level-based deep reinforcement learning method for routing, modulation, and spectrum assignment of elastic optical networks","authors":"Chengsheng Liang, Yuqi Tu, Yue-Cai Huang","doi":"10.1117/12.3007879","DOIUrl":"https://doi.org/10.1117/12.3007879","url":null,"abstract":"Deep reinforcement learning (DRL) has been introduced in routing, modulation and spectrum assignment (RMSA) of the elastic optical networks. Since the DRL agent’s learning is based on the state it observes and the reward it receives, key information should be embedded in the state and the reward. In previous studies, the observed and feedback information is limited. In this paper, we propose a busyness level-based DRL method for the RMSA of the elastic optical networks. Since the busyness of the links or transmission paths highly affects the performance, we believe the busyness information should be perceived by the agent to learn a good RMSA policy. Specifically, we define two indicators to quantify busyness level, and then combine these two indicators into the design of reward and state. Simulation results show that our approach works better than the case that busyness is not","PeriodicalId":502341,"journal":{"name":"Applied Optics and Photonics China","volume":"11 3","pages":"1296624 - 1296624-7"},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139172840","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}
Yipeng Mei, Yuxin Ma, Jun Lu, Tongtong Yang, Yue-chun Shi, Lianyan Li, Xin Wang, Ming Li, Rulei Xiao, Xiangfei Chen
A 16-channel optical transmitter chip with a digital transmission capacity up to 1.6 Tb/s has been demonstrated. In this chip, a 16-wavelength III–V DFB laser array (MLA), a silicon Mach-Zehnder interferometer (MZI) modulator array and a 16-channel fiber array are hybrid integrated by photonic wire bonding (PWB) technique. The MLA based on reconstruction-equivalent-chirp (REC) technique proves a good wavelength spacing uniformity of all wavelengths. Each unit laser with 1.2 mm cavity length in the MLA exhibits good single-longitudinal-mode operation with the output power over 18 dBm at an injection current of 300 mA. Spectral measurements show the channels coincide well with the designed 200 GHz spacing, with wavelength deviations within a range of ±0.2 nm. Based on PWB technique, three chips mentioned above are integrated optically on one Wu-Cu substrate as a 16-channel optical transmitter. The largest output power of optical transmitter is 1.5 mW and all channels still keep good single mode outputs after PWB integration. The tested modulation speed of each channel is up to 100 Gb/s, which implies the total transmission capacity of this device is 1.6 Tb/s.
{"title":"Multi-wavelength laser array based on REC integrated with silicon-based devices by photonic wire bonding","authors":"Yipeng Mei, Yuxin Ma, Jun Lu, Tongtong Yang, Yue-chun Shi, Lianyan Li, Xin Wang, Ming Li, Rulei Xiao, Xiangfei Chen","doi":"10.1117/12.3007834","DOIUrl":"https://doi.org/10.1117/12.3007834","url":null,"abstract":"A 16-channel optical transmitter chip with a digital transmission capacity up to 1.6 Tb/s has been demonstrated. In this chip, a 16-wavelength III–V DFB laser array (MLA), a silicon Mach-Zehnder interferometer (MZI) modulator array and a 16-channel fiber array are hybrid integrated by photonic wire bonding (PWB) technique. The MLA based on reconstruction-equivalent-chirp (REC) technique proves a good wavelength spacing uniformity of all wavelengths. Each unit laser with 1.2 mm cavity length in the MLA exhibits good single-longitudinal-mode operation with the output power over 18 dBm at an injection current of 300 mA. Spectral measurements show the channels coincide well with the designed 200 GHz spacing, with wavelength deviations within a range of ±0.2 nm. Based on PWB technique, three chips mentioned above are integrated optically on one Wu-Cu substrate as a 16-channel optical transmitter. The largest output power of optical transmitter is 1.5 mW and all channels still keep good single mode outputs after PWB integration. The tested modulation speed of each channel is up to 100 Gb/s, which implies the total transmission capacity of this device is 1.6 Tb/s.","PeriodicalId":502341,"journal":{"name":"Applied Optics and Photonics China","volume":"133 ","pages":"129661Y - 129661Y-5"},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139173004","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}
This paper proposed an infrared hyperspectral band selection algorithm based on autoencoder Combining neural network, deep learning and other methods, an infrared hyperspectral band selection algorithm based on autoencoder is proposed to reduce the dimension of infrared hyperspectral images without loss of information. Encode infrared hyperspectral data to obtain dimensionality reduced data, decode the dimensionality reduced data to obtain reconstructed hyperspectral data, and use a band selection evaluation method based on average reconstruction error to evaluate the effectiveness of this band selection method. Based on the measured infrared hyperspectral data, the performance of this algorithm is compared with that of the band selection algorithm based on spatial dimension inter class separability and spectral dimension inter class separability. Experimental results have shown that the algorithm proposed in this paper outperforms the other two algorithms and has low reconstruction error in band selection results.
{"title":"Research on infrared hyperspectral band selection algorithm based on autoencoder","authors":"Chang Liu, Guangping Wang","doi":"10.1117/12.3007251","DOIUrl":"https://doi.org/10.1117/12.3007251","url":null,"abstract":"This paper proposed an infrared hyperspectral band selection algorithm based on autoencoder Combining neural network, deep learning and other methods, an infrared hyperspectral band selection algorithm based on autoencoder is proposed to reduce the dimension of infrared hyperspectral images without loss of information. Encode infrared hyperspectral data to obtain dimensionality reduced data, decode the dimensionality reduced data to obtain reconstructed hyperspectral data, and use a band selection evaluation method based on average reconstruction error to evaluate the effectiveness of this band selection method. Based on the measured infrared hyperspectral data, the performance of this algorithm is compared with that of the band selection algorithm based on spatial dimension inter class separability and spectral dimension inter class separability. Experimental results have shown that the algorithm proposed in this paper outperforms the other two algorithms and has low reconstruction error in band selection results.","PeriodicalId":502341,"journal":{"name":"Applied Optics and Photonics China","volume":"40 2","pages":"129600D - 129600D-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139173190","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}
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