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Physics-constrained deep-inverse point spread function model:toward non-line-of-sight imaging reconstruction
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作者 Su Wu chan huang +4 位作者 Jing Lin Tao Wang Shanshan Zheng Haisheng Feng Lei Yu 《Advanced Photonics Nexus》 2024年第2期90-99,共10页
Non-line-of-sight(NLOS)imaging has emerged as a prominent technique for reconstructing obscured objects from images that undergo multiple diffuse reflections.This imaging method has garnered significant attention in d... Non-line-of-sight(NLOS)imaging has emerged as a prominent technique for reconstructing obscured objects from images that undergo multiple diffuse reflections.This imaging method has garnered significant attention in diverse domains,including remote sensing,rescue operations,and intelligent driving,due to its wide-ranging potential applications.Nevertheless,accurately modeling the incident light direction,which carries energy and is captured by the detector amidst random diffuse reflection directions,poses a considerable challenge.This challenge hinders the acquisition of precise forward and inverse physical models for NLOS imaging,which are crucial for achieving high-quality reconstructions.In this study,we propose a point spread function(PSF)model for the NLOS imaging system utilizing ray tracing with random angles.Furthermore,we introduce a reconstruction method,termed the physics-constrained inverse network(PCIN),which establishes an accurate PSF model and inverse physical model by leveraging the interplay between PSF constraints and the optimization of a convolutional neural network.The PCIN approach initializes the parameters randomly,guided by the constraints of the forward PSF model,thereby obviating the need for extensive training data sets,as required by traditional deep-learning methods.Through alternating iteration and gradient descent algorithms,we iteratively optimize the diffuse reflection angles in the PSF model and the neural network parameters.The results demonstrate that PCIN achieves efficient data utilization by not necessitating a large number of actual ground data groups.Moreover,the experimental findings confirm that the proposed method effectively restores the hidden object features with high accuracy. 展开更多
关键词 non-line-of-sight imaging point spread function model deep learning
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多角度偏振云检测及云参数反演 被引量:13
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作者 常钰阳 孙斌 +2 位作者 黄禅 洪津 乔延利 《光学学报》 EI CAS CSCD 北大核心 2020年第11期11-21,共11页
高分五号卫星多角度偏振探测仪(DPC)是国内首台具备业务化多光谱多角度偏振探测能力的星载遥感器。发展了一套针对DPC观测数据的处理算法,可获取观测区域上空云检测结果、相态分布和云光学厚度。利用670 nm、865 nm反射率、490 nm几何... 高分五号卫星多角度偏振探测仪(DPC)是国内首台具备业务化多光谱多角度偏振探测能力的星载遥感器。发展了一套针对DPC观测数据的处理算法,可获取观测区域上空云检测结果、相态分布和云光学厚度。利用670 nm、865 nm反射率、490 nm几何归一化偏振辐亮度和865 nm线偏振度进行云检测;利用865 nm归一化偏振辐亮度进行相态识别;利用670 nm、865 nm反射率以及相态识别结果反演云光学厚度。由于尚未获取可反演的DPC L1级观测数据,仅将算法应用于地球反射率多角度偏振观测仪(POLDER)数据,以验证算法有效性。对比POLDER云产品,得到判云一致性和判晴一致性分别为93.3%和92.9%;水云、冰云和混合相态判别一致性分别为87.4%,76.6%和22.8%;云光学厚度的相关系数为0.89,故该算法可行有效。该算法为DPC发展业务化云产品提供参考。 展开更多
关键词 大气光学 多角度偏振观测 云检测 云相态 云光学厚度 多角度偏振探测仪(DPC) 地球反射率多角度偏振观测仪(POLDER)
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Adaptive Operator-Based Spectral Deconvolution With the Levenberg-Marquardt Algorithm 被引量:2
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作者 chan huang Feinan CHEN +3 位作者 Yuyang chanG Lin HAN Shuang Li Jin HONG 《Photonic Sensors》 SCIE EI CSCD 2020年第3期242-253,共12页
Spectral distortion often occurs in spectral data due to the influence of the bandpass function of the spectrometer.Spectral deconvolution is an effective restoration method to solve this problem.Based on the theory o... Spectral distortion often occurs in spectral data due to the influence of the bandpass function of the spectrometer.Spectral deconvolution is an effective restoration method to solve this problem.Based on the theory of the maximum posteriori estimation,this paper transforms the spectral deconvolution problem into a multi-parameter optimization problem,and a novel spectral deconvolution method is proposed on the basis of Levenberg-Marquardt algorithm.Furthermore,a spectral adaptive operator is added to the method,which improves the effect of the regularization term.The proposed methods,Richardson-Lucy(R-L)method and Huber-Markov spectroscopic semi-blind deconvolution(HMSBD)method,are employed to deconvolute the white light-emitting diode(LED)spectra with two different color temperatures,respectively.The correction errors,root mean square errors,noise suppression ability,and the computation speed of above methods are compared.The experimental results prove the superiority of the proposed algorithm. 展开更多
关键词 Optical data processing SPECTROMETER DECONVOLUTION
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The research of laser-based rapid measurement system for scintillator neutron detectors arrays
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作者 Bin Tang Qian Yu +7 位作者 chan huang Hai-yun Teng Yan-feng Wang Hong Xu Yun-tao Liu Lin Qiu Guang-you Wei Zhi-jia Sun 《Radiation Detection Technology and Methods》 CSCD 2020年第4期400-406,共7页
Purpose Scintillator Neutron Detectors Arrays(SNDA)were successfully installed at General Purpose Powder Diffractome-ter(GPPD)at the China Spallation Neutron Source(CSNS).The inhomogeneity of the detection efficiency ... Purpose Scintillator Neutron Detectors Arrays(SNDA)were successfully installed at General Purpose Powder Diffractome-ter(GPPD)at the China Spallation Neutron Source(CSNS).The inhomogeneity of the detection efficiency in each detector module,which caused by the gain nonuniformity of the multi-anode photo-multiplier tubes(MA-PMTs)and the inconsistency of the wave-length shifting fibers in collecting scintillation photons,need to be mitigated before the installation.Methods An automated rapid measurement system based on the blue laser and the two-dimensional mobile platform was developed to calibrate the light response of each channel in detector modules.According to the test results of this system,the electronics threshold of each channel of the SNDA is adjusted.Before the installation of the all 40 SNDA modules in GPPD,the electronics thresholds of each channel are adjusted according to the measurement results of this rapid measurement system.Results and Conclusion Compared with the unadjusted detector module,the adjusted one obtained a better uniformity of the neutron detection efficiency.The inhomogeneity of the detection efficiency is improved from 27.4%to 10.9%.The test result of the diffraction peak of the standard sample Si showed that the adjusted SNDA works well in GPPD. 展开更多
关键词 SYSTEM SHIFTING LASER
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