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1、基于互补特征的纹理图像检索摘要:针对互补特征可以有效地改善图像检索系统性能的特点,提出一种在改进contourlet变换域采用l1能量与广义高斯分布参数特征的纹理图像检索方法。首先,应用改进的方法对方向子带系数进行广义高斯统计建模。然后,分别单独利用各个特征和相应的相似性测度进行检索。最后,基于直接的相似性测度和,采用这两种互补的特征进行检索。实验结果表明,和采用单一特征相比较,互补特征由于充分地反映了图像的结构信息和随机分布信息,从而有效地提高了纹理图像数据库的平均检索率。关键词:改进的co
2、ntourlet变换;建模;l1能量;广义高斯分布;互补特征;纹理图像检索textureimageretrievalbasedoncomplementaryfeaturesquhuai.jing*schoolofinformationandelectricengineering,shandongjianzhuuniversity,jinanshandong250101,chinaabstract:becausetheperformanceoftheimageretrievalsyste
3、mcouldbeeffectivelyimprovedusingthecomplementaryfeatures,aretrievalmethodofthetextureimageusingl1energyandgeneralizedgaussiandistributionparameterfeatureswasproposedintheimprovedcontourlettransformdomain.firstly,thedirectionalsubbandcoefficientswere
4、modeledasgeneralizedgaussiandistributionusinganimprovedapproach.then,thetextureimageswererespectivelyretrievedbasedonthesinglefeatureandthecorrespondingsimilaritymeasurement.lastly,usingthecomplementaryfeaturesandthedirectsummationoftheirsimilaritymeas
5、urements,thetextureimageswereretrieved.theexperimentalresultsshowthat,comparedwithsinglefeature,theaverageretrievalratesofthetextureimagedatabaseareeffectivelyimprovedbythecomplementaryfeaturesduetofullyrepresentingthestructuralinformationandtherandomd
6、istributioninformation.becausetheperformanceoftheimageretrievalsystemcouldbeeffectivelyimprovedbyusingthecomplementaryfeatures,aretrievalmethodofthetextureimageusingl1energyandgeneralizedgaussiandistributionparameterfeatureswasproposedintheimprovedc
7、ontourlettransformdomain.firstly,thedirectionalsubbandcoefficientswentthroughgeneralizedgaussianmodelingwithanimprovedapproach.then,thetextureimageswererespectivelyretrievedbasedonthesinglefeatureandthecorrespondingsimilaritymeasurement.lastly,usingthe
8、complementaryfeaturesandthedirectsummationoftheirsimilaritymeasurements,thetextureimageswereretrieved.theexperimentalresultsshowthat,comparedwithsinglefeature,theaverageretrievalratesofthetextureimagedatabaseareeffectivelyimprovedbythec