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Study On Electro-Optical Detection Of Dim Object In Strong Background

Posted on:2005-10-06Degree:MasterType:Thesis
Country:ChinaCandidate:J W ZouFull Text:PDF
GTID:2168360155471861Subject:Electronic Science and Technology
Abstract/Summary:PDF Full Text Request
Electro-optical detection ,as a highly accurate method,plays a key role in space object detection and surveillance.How to detect target in strong background has always been a choke point in limiting electro-optical equipment's ability.Study of how to enhancing detection of target in strong background is of great significance to improve the electro-optical equipment's level of work all day and space detection and surveillance ability.After analysis of object's optical characteristics and electro-optical detection technology,the thesis focus on low Signal-to-Noise Ratio(SNR) target extraction and spectral filtering technology which are considered as the key technology in detection of dim target in strong background.The correlative knowledge,research content and delevoping direction of object and environment's optical characteristics are introduced,specially we analyze the optical scattering characteristics and spectral characteristics according to the technique flow in the thesis.As to detection of low SNR target,after analysis of low SNR small target's characteristics and baisic detection methods,we bring forward a small target extraction method based on morphologic filtering and image flow. In the thesis ,we discuss the principle and implement of the method in detail and bring out the simulation and experiment results.According to the observation and data processing results of sky background ,we analyze the brightness and spectral distribution of daytime sky and demonstrate the efficiency of spectral filtering technology in enhancing SNR.The concrete application of spectral filtering technology in electro-optical detection is specially discussed in the thesis.
Keywords/Search Tags:Electro-optical detection, Strong background, Low SNR, Morphological filtering, Image flow, Spectral filtering
PDF Full Text Request
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