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Information Extraction of Bionic Camera-Based Polarization Navigation Patterns Under Noisy Weather Conditions 被引量:1

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摘要 Light polarization is the phenomenon that describes the oscillations and orientations of the light waves.Polarized light is a source of substantial cue for navigation in many marine and land-dwelling animals.This work investigates the challenges of obtaining information regarding polarization under various conditions by observing the phenomenology of the ommatidium in many insects.Noisy conditions can be because of haze or the presence of clouds in the atmosphere.Aerosol molecules are greater in volume and scale in such atmospheric conditions.When sunlight crosses through these molecules of aerosol,its polarization information is distorted.The distorted pattern has a little or no information on neutral points of light polarization.On the basis of the relationship bet ween wavelength of sunlight and polarization,we propose a novel hue based color mixing(HBCM)model to calculate the polarization information and orientation information more accurately and robustly.This method improves the symmetries of polarization patterns and eliminates the effect of noises.Symmetries of polarization patterns are compared with red,green and blue(RGB)spectrum and these differences are quantified and compared especially under high noisy weather conditions.
作者 AH SAN Muhammad CAI Yunze ZHANG Weidong AH SAN Muhammad;蔡云泽;张卫东(Department of Automation,Ministry of Education of China,Shanghai Jiao Tong University,Shanghai 200240,China;Key Laboratory of System Control and Information Processing,Ministry of Education of China,Ministry of Education of China,Shanghai Jiao Tong University,Shanghai 200240,China;Key Laboratory of Marine Intelligent Equipment and System,Ministry of Education of China,Shanghai Jiao Tong University,Shanghai 200240,China)
出处 《Journal of Shanghai Jiaotong university(Science)》 EI 2020年第1期18-26,共9页 上海交通大学学报(英文版)
基金 the National Natural Science Foundation of China(No.61627810) the Joint Fund of Advanced Aerospace Manufacturing Technology Research of China(No.USCAST2016)。
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