基于shearlet变换的图像分割与边缘检测分析

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1、辽宁师范大学硕士学位论文(3)OnthebasisoftheprobabilityruleoftheShearletcoefficients,thispeppercontinuousstatisticsthejointstatisticalproperritiesofthenonsubsampledShearlettransformcoefficients,itanalyzestheShearletcoefficientshavethesimilaritystatisticalcharacteristicwitht

2、hewaveletcoefficientsandContourletcoefficients,thatispersistenceandaggregation.AndthenestablishesthenonsubsampledShearlettransformdomainhiddenMarkovmodel,thismodelconsidersthecoefficientdependencyatthesamescaleaswellasthefather-childrencoefficientdependencyatt

3、hedifferentscales.Thismodelobtainstheagoodeffectintheimagedenoising.KeyWords：ShearletTransform；Vector-valuedC-VModel；GaussianMixtureModel；HiddenMarkovTreeModel；ImageSegmentation；ImageEdgeDetectionIII万方数据基于Shearlet变换的图像分割与边缘检测研究目录摘要.............................

4、................................................................................................IAbstract.....................................................................................................................................II1绪论.................

5、........................................................................................................................11.1研究的背景和意义...................................................................................................11.2本论文涉及的图像处理内容.............

6、........................................................................21.2.1图像分割技术..................................................................................................21.2.2图像边缘检测技术................................................................

7、..........................41.2.3图像去噪技术..................................................................................................51.3图像处理中变换域方法的发展简述..........................................................................61.4文章结构.......................

8、..............................................................................................92Shearlet变换的数学理论.....................................................................