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1、Rate-distortionanalysisforvectorquantizationbasedonavariableblock-sizeclassicationmodelM.H.Lee,K.N.NganandG.A.CrebbinDepartmentofElectricalandElectronicEngineeringTheUniversityofWesternAustraliaNedlands,WA6907,AustraliaABSTRACTVectorquantization(VQ)basedonaxedblock-sizeclassicati
2、on(FBSC)model,whichisknownasclassiedVQ(CVQ),oersausefulsolutionfortheedgedegradationproblemofconventionalimageVQ.Inourpreviouswork,wehavedevelopedaVQtechniquebasedonavariableblock-sizeclassication(VBSC)model,inwhichanimageissegmentedintoblocksofvarioussize,andeachsegmentedregioni
3、sencodedatadierentrateaccordingtoitslevelofdetail.Thelow-detailregionsoftheimageconsistofvariablesizeblocksandareencodedatverylowbitrateswithlittleperceptualdegradation.High-detailregions,whichareisolatedintothesmallestblocks,areclassiedintovariousedgesofwhicheachisseparatelyencod
4、ed.Inthispaper,arate-distortionfunction(RDF),R(D),ispresentedforaVBSCmodel.WeobtainatheoreticalR(D)boundontheperformanceofVQbasedonaVBSCmodel.ItistheoreticallyprovedthattheR(D)boundoftheVBSCmodelislowerthanthoseoftheGaussianmodelandtheFBSCmodel.WealsoexperimentallyevaluateaRDFforthe
5、VBSCmodelandcomparewiththetheoreticalRDF.Thereisagapofabout0.1bppbetweenthetheoreticalRDFandtheexperimentalRDFinVBSCmodel-basedVQcoding.Weexpectthatthisgapcanbereducedbysubsequentlyemployinganentropycoder.Keywords:imagecoding,vectorquantization,rate-distortionfunction1.INTRODUCTION1
6、SinceRamamurthiandGershoproposedavectorquantization(VQ)techniquebasedonaclassicationmodel,2?5whichisknownasclassiedVQ(CVQ),severalpapershavedemonstratedthatCVQoersanexcellentsolutionfortheedgedegradationproblemofconventionalimageVQ.Theuseofasmallerblocksizeinblockcodinghasbeenkno
7、wntoleadtobettersubjectivequality,andmoststudiesinVQandCVQhavefocussedondevelopingalgorithmsthatusexedsmall-sizedblocks,typically44.However,theblocksizeinVQistoosmalltotakeadvantageofthefactthatfewerbitsarerequiredtoencodelow-detailregions,whichusuallyoccupylargeareasinanimage.Rec
8、ently,therehasbeenm