球面复眼多通道信息融合

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1、中国科学技术大学硕士学位论文球面复眼多通道信息融合姓名：张浩申请学位级别：硕士专业：精密机械与仪器指导教师：王克逸20100602摘要ABSTRACTCompoundeyeismoreandmoreconcernedbyacademiaandindustry,duetoitsadvantageoflargeviewfield,highagility,andmuti-channels.Thereforescholarsofmanycountriesbegintofocusontheirinterestsintotheresearchofartificialcompoundeye.Howe

2、ver,theadvantageofcompoundeyeisusuallylimitedbecauseoftherestrictionoffabricationtechnique.Thestructureofplanercompoundeyelimitsitsfieldofview.Althoughsphericalcompoundeyeisverysimilarwiththenaturecompoundeyeinlargefieldofview,theplanerimagesensorrequiresthateveryeyeletlensinthesphericalsurfaceh

3、asdifferentfocuslengthanddifferentprofilewhichisusuallyaspherical.Furthermore,theasphericallensisverydifficulttofabricatebyusingtraditionalfabricationtechnique.Ourlabdesignedanewartificialcompoundeyemodelbasedonthenaturecompound-eyestructure.Thismodelhandlesthecontradictionbetweenthesphericaldom

4、eandplanerimagesensor.Itsopticalperformancecanbeoptimizedbasedontheliquidlensfabricationsystemdevelopedbyourlab.Inthisworkreported,theopticalperformanceofthismodelisanalyzed.Weproposethetechniqueofimagedenoisingandimagetransferringintheimagepreprocessingsection,includingsub-pixelmethodandNeuraln

5、etworkarithmeticwhichsolvetheproblemofaberrationandnoiseincompoundeyeimagingprocess.Moreover,weproposemulti-channelinformationinfusingarithmetic,whichcontainsimagemosaic,superresolutionimagingandmovingobjectdetection.Toexaminethefeasibilityofthearithmeticinimagepreprocessingandmulti-channelinfor

6、mationinfusing,weperformedsimulationbyusingMatlab,andbuilttheexperimentalplatformforfurtherobservation.Bothofresultsshowthatneuralnetworkhasgoodperformanceinthenonlinearcalibrationandthecenterofgravitymethodcanrecordthepositionofspotprecisely.Besides,theresultsalsoshowthatalthoughcompoundeyeisan

7、opticalsystemthatsacrificeitsspatialresolutiontoimproveitsfieldofview,ourcompoundeyemodelcanstilldetecttheprecisepositionofmovingobject.Ourmodelwillhavehasgoodapplicationforeground.KeyWords:compoundeye,neuralnetwork,centerof