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1、ISSN1000-9825,CODENRUXUEWE-mail:jos@iscas.ac.cnJournalofSoftware,Vol.20,No.12,December2009,pp.3240−3253http://www.jos.org.cndoi:10.3724/SP.J.1001.2009.03649Tel/Fax:+86-10-62562563©byInstituteofSoftware,theChineseAcademyofSciences.Allrightsreserved.∗基于近似高斯金字塔的视觉注意模型快速算法
2、1+112张国敏,殷建平,祝恩,毛玲1(国防科学技术大学计算机学院,湖南长沙410073)2(国防科学技术大学电子科学与工程学院,湖南长沙410073)FastVisualAttentionModelAlgorithmBasedonApproximateGaussianPyramids1+112ZHANGGuo-Min,YINJian-Ping,ZHUEn,MAOLing1(SchoolofComputerScience,NationalUniversityofDefenseTechnology,Changsha410073,Chi
3、na)2(SchoolofElectronicScienceandEngineering,NationalUniversityofDefenseTechnology,Changsha410073,China)+Correspondingauthor:E-mail:Guomin_Zhang@163.comZhangGM,YinJP,ZhuE,MaoL.FastvisualattentionmodelalgorithmbasedonapproximateGaussianpyramids.JournalofSoftware,2009,20
4、(12):3240−3253.http://www.jos.org.cn/1000-9825/3649.htmAbstract:Classicalsaliency-basedvisualattentionmodelsareadaptedforembeddingreal-timesystemswithlesstimeandspacecostsbasedonapproximateGaussianpyramidsoftheinputimage.Firstly,thecircularwindowanddiscreteGaussianconv
5、olutionareapproximatedbyrectangularwindowandrectangularaverageoperatorrespectively.Then,rectangularaverageoperatorisimplementedthrough“rowaccumulationfollowedbycolumnaccumulation”.Andconspicuitymapsofeachchannelarecalculatedandsampledatdesiredintervalsdirectlywithlinea
6、rcomputationalcomplexityonthenumberoftheinputpixels.Atlast,afastalgorithmforinhibitingthesaliencyofextractedregionsinthesaliencymapisproposed.ExperimentalresultsintheimagesfromBerkeleysegmentationdatasetvalidatethattheproposedmethodshavemuchlesscomputationalcostswithac
7、ceptableoutputtingerrors.Thetwoapproximatemethodsinthispapercanalsobeappliedinotherimageprocessingproblemsinembeddingreal-timesystems.Keywords:saliency;visualattention;approximateGaussianpyramids;imageprocessing摘要:利用输入图像的近似高斯金字塔,将经典的基于显著性的视觉注意模型改造为时空开销更小的版本,从而使其更加适合在嵌入
8、式实时系统中实现.首先采用矩形窗口近似圆形窗口,矩形平均算子近似高斯卷积核;然后采用“先做行累加,再做列累加”的方法来实现矩形平均算子,并直接采样计算出各个特征通道的显著性分布图,该算法关于输入图像像素点个数具有线性时间复杂度;最后,
