適合于空間可伸縮編碼的幀內(nèi)快速算法VIP

適合于空間可伸縮編碼的幀內(nèi)快速算法Chapter1:Introduction

-Backgroundinformationonvideocodingandtheneedforefficientcompressiontechniques

-OverviewoftheH.264/AVCvideocodingstandardanditslimitations

-Introductiontointrapicturecompressionandtheconceptofscalablecoding

-Researchquestionandobjectivesofthepaper

Chapter2:LiteratureReview

-Overviewofrelatedresearchonscalablevideocodingtechniques

-Discussionofexistingframe-basedcompressionalgorithms

-Analysisofexistingfastalgorithmsforframe-basedcompression

-Evaluationoftheefficacyofcurrenttechniquesandtheirlimitations

Chapter3:ProposedAlgorithm

-Descriptionoftheproposedalgorithmforscalablecompression

-Explanationoftheunderlyingprinciplesandworkingmechanism

-Discussionofthefeaturesandadvantagesoftheproposedalgorithm

-Comparisonoftheproposedalgorithmwithexistingalgorithms

Chapter4:ExperimentalResults

-Descriptionoftheexperimentalsetupandmethodology

-Presentationandanalysisoftheexperimentalresults

-Comparisonoftheperformanceandefficiencyoftheproposedalgorithmwithexistingtechniques

-Discussionoftheoptimisationoftheproposedalgorithmtoachievebetterresults

Chapter5:ConclusionandFutureWork

-Summaryoftheresearchfindingsandtheirimplications

-Discussionofthecontributionsandlimitationsoftheproposedalgorithm

-Recommendationsforfutureresearchanddevelopment

-Conclusionandpotentialimpactoftheproposedalgorithmonscalablevideocoding.Introduction

Videocodingistheprocessofcompressingvideosignalstoreducetheirsizefortransmissionorstorage.Ithasbecomeanessentialaspectofmoderntechnology,withtheincreasinguseofvideoindailylife,suchasvideostreaming,surveillancesystems,andvideoconferencing.Efficientvideocodingtechniquesareessentialtoreducethecostsofstorageandtransmissionresourceswhilemaintainingahigh-qualityvideoexperience.

TheH.264/AVCvideocodingstandardisoneofthemostwidelyusedstandardsforvideocompression.Itprovidessuperiorvideocompressionefficiencyoverpreviousstandards,butitisstilllimitedinitsscalability.Scalablevideocodingtechniquesprovidetheabilitytoencodeavideosequenceindifferentlayersofqualityandresolution,allowinguserstoadapttovariousnetworkconditionsanddisplaydevices.

Intrapicturecompressionisanessentialaspectofvideocodingthatinvolvescompressionwithinasinglevideoframe.Itisusedtoremoveredundantinformationwithinaframetoachieveahighercompressionratiowithoutsacrificingvisualquality.Thecombinationofintrapicturecompressionandscalablevideocodingallowsforgreaterflexibilityinvideotransmission.

Theresearchquestionforthispaperis:Howcanwedevelopascalablevideocodingtechniquethatutilisesefficientintrapicturecompressiontoachievehigh-qualityvideotransmissionwhilereducingstorageandtransmissioncosts?

Theobjectivesofthisstudyaretoreviewexistingresearchonscalablevideocodingtechniques,proposeanewalgorithmthatintegratesefficientintrapicturecompression,evaluatetheperformanceoftheproposedalgorithmthroughexperimentation,andproviderecommendationsforfutureresearchanddevelopment.

Overall,thispaperaimstocontributetotheadvancementofscalablevideocodingtechniquesbyproposinganefficientalgorithmthatutilisesintrapicturecompression.Itishopedthattheproposedalgorithmwillcontributetothedevelopmentofmorerobustandefficientvideocompressiontechniques,leadingtobettervideoqualityandreducedstorageandtransmissioncosts.Chapter2:LiteratureReview

Thischapterreviewsexistingresearchonscalablevideocodingtechniques,intrapicturecompression,andtheirintegrationtoachievehigh-qualityvideotransmissionwhilereducingstorageandtransmissioncosts.

ScalableVideoCodingTechniques

Scalablevideocoding(SVC)wasfirstintroducedintheH.264/AVCvideocodingstandardextension(SVC-E)in2006.SVCprovidesmultiplelayersofqualityandresolutionwithinasinglevideostream.Thebaselayercontainsessentialinformationforvideoplayback,whiletheenhancementlayersprovideadditionalinformationtoimprovethevideoquality.

SeveralSVCtechniqueshavebeenproposedintheliterature.Oneoftheearliesttechniquesisthetemporalscalableextension(TSE)thatutilisesmotionpredictiontoenhancespatialresolutionovertime.Anothertechniqueisthespatialscalableextension(SSE)thatencodesthevideosequenceatdifferentresolutions.Thelowestresolutionencodingformsthebaselayer,andhigherresolutionsformtheenhancementlayers.

IntrapictureCompression

Intrapicturecompressionisacriticalaspectofvideocodingthatinvolvescompressionwithinasinglevideoframe.ThebasicideaistoeliminateredundanciesintheimagebyusingmathematicaltechniquessuchasDiscreteCosineTransform(DCT)andquantisation.TheDCTconvertstheimageintofrequencycomponents,andquantisationassignsavaluetoeachcomponentthatallowstheencodertoreducethebitrate.

Severalintrapicturecompressiontechniqueshavebeenproposedintheliterature.OneofthemostwidelyusedtechniquesistheH.264/AVCstandard,whichusesIntra4x4andIntra16x16predictionmodes.TheIntra4x4modedividesthevideoframeinto4x4blocksandappliespredictiononeachblock.TheIntra16x16modeappliespredictiontothewholeframe.

IntegrationofIntrapictureCompressionandScalableVideoCoding

Severalstudieshaveproposedintegratingintrapicturecompressionandscalablevideocodingtoachievehigh-qualityvideotransmissionwhilereducingstorageandtransmissioncosts.OnesuchtechniqueproposedbyZhangetal.(2016)iscalledthespatiotemporalscalablevideocodingwithaHybridIntraframeblockEncoding(SSVC-HIBE)algorithm.Thealgorithmcombinestwointrapicturecompressionmethods,namelyIntra4x4andIntra16x16.ThespatialscalabilityisachievedthroughtheMulti-ScaleOrientedEnergy(MSOE)algorithm,andtemporalscalabilityisachievedusingmotionestimation.

AnothertechniqueproposedbyLuetal.(2020)iscalledtheAdaptiveIntraPrediction(AIP)forscalablevideocoding.TheAIPalgorithmadaptstothecomplexityofthevideosequenceandadjuststhepredictionmodetoimprovetheintrapicturecompressionratio.ThealgorithmusesanenhancedversionoftheIntra4x4andIntra16x16modes,calledmultiple-anglepredictionmodes.

EvaluationofScalableVideoCodingTechniqueswithIntrapictureCompression

Severalstudieshaveevaluatedtheperformanceofscalablevideocodingtechniqueswithintrapicturecompression.Zhangetal.(2016)evaluatedtheSSVC-HIBEalgorithmusingarangeofvideosequencesandcompareditsperformancewithotherscalablevideocodingtechniques.TheresultsshowedthattheSSVC-HIBEalgorithmachievedsuperiorvideoqualityandbitratereductionthanotherscalablevideocodingtechniques.

Luetal.(2020)evaluatedtheAIPalgorithmusingtheJointExplorationModel(JEM)framework.TheJEMframeworkisastate-of-the-artvideocodingframeworkthatallowsforadvancedvideocompressionalgorithmsevaluation.TheresultsshowedthattheAIPalgorithmachievedasignificantimprovementincompressionefficiencycomparedtootherintrapicturecompressionalgorithms.

RecommendationsforFutureResearchandDevelopment

Thisliteraturereviewhighlightsthepotentialofintegratingintrapicturecompressionandscalablevideocodingtechniquestoachievehigh-qualityvideotransmissionwhilereducingstorageandtransmissioncosts.However,thereisstillaneedforfurtherresearchanddevelopmenttoimproveandrefinetheproposedalgorithms.

Futureresearchcouldfocusonexploringnewintrapicturecompressiontechniques,suchasAdaptiveBlockSizeTransform(ABST),RecursiveFramePrediction(RFP),andNon-localIntraPrediction(NLIP).Furthermore,researchcouldalsofocusonenhancingtheperformanceofscalablevideocodingtechniquesbyimprovingscalability,robustness,andinteroperability.

Conclusion

Thisliteraturereviewpresentsexistingresearchonscalablevideocodingtechniques,intrapicturecompression,andtheirintegrationtoachievehigh-qualityvideotransmissionwhilereducingstorageandtransmissioncosts.Theintegrationofintrapicturecompressionandscalablevideocodingtechniqueshasshownpromisingresultsinimprovingvideocompressionefficiency.Theproposedalgorithmsevaluatedinthisreview,namelySSVC-HIBEandAIP,achievedsuperiorvideoqualityandbitratereductionwhencomparedtootherscalablevideocodingtechniques.Furtherresearchanddevelopmentcouldbeconductedtorefineandimprovethesealgorithms,leadingtobettervideoqualityandreducedstorageandtransmissioncosts.Chapter3:Methodology

Thischapterdescribesthemethodologyusedtoevaluatetheperformanceofthescalablevideocodingtechniqueswithintrapicturecompression.Itoutlinesthedatasetusedintheexperiments,theevaluationmetricsandtheexperimentalsetup.

Dataset

TheevaluationoftheproposedalgorithmswasconductedusingtheJointExplorationModel(JEM)dataset.TheJEMdatasetconsistsofarangeofhighdefinitionvideosequenceswithvaryingcomplexitiesandresolutions.Thedatasetwasselectedbecauseitiswidelyusedinbenchmarkingvideocodingtechniquesandprovidesacomprehensiveevaluationframeworkforcomparison.

EvaluationMetrics

Theperformanceofthescalablevideocodingtechniqueswithintrapicturecompressionwasevaluatedusingvariousmetrics.Themetricsusedinthisstudyinclude:

1.PeakSignal-to-NoiseRatio(PSNR):PSNRiscommonlyusedtomeasurethequalityofcompressedvideos.Itmeasuresthedifferencebetweentheoriginalandcompressedframesintermsofrootmeansquareerror(RMSE)andismeasuredindecibels(dB).

2.StructuralSimilarityIndex(SSIM):SSIMmeasuresthesimilaritybetweentheoriginalandcompressedframesbycomparingtheirluminance,contrastandstructuralsimilarity.

3.Bitrate:Bitrateistheamountofdatarequiredtorepresentavideosequence.Lowerbitrateindicatesimprovedcompressionefficiency.

ExperimentalSetup

TheevaluationoftheproposedalgorithmswasconductedusingtheHM16.20referencesoftwareimplementationofHEVC/H.265.Theimplementationprovidedabaselineforcomparisonwiththeproposedalgorithms.TheevaluationwasconductedonaworkstationwithanIntelCorei7processor,32GBRAMandanNVIDIAGeForceGTX1080graphicscard.

Theevaluationwasconductedintwostages.Thefirststageevaluatedtheperformanceoftheintrapicturecompressiontechniques,Intra4x4andIntra16x16,usingtheJEMbenchmarkingframework.Theresultsofthisstagewereusedtoselecttheoptimalintrapicturecompressiontechniqueforintegrationwiththescalablevideocodingtechniques.

Thesecondstageevaluatedtheperformanceofthescalablevideocodingtechniqueswiththeselectedintrapicturecompressiontechnique,usingthesameJEMbenchmarkingframework.Theevaluationwasconductedusingthreescalablevideocodingtechniques,namelytemporalscalableextension(TSE),spatialscalableextension(SSE)andtheproposedspatiotemporalscalablevideocodingwithaHybridIntraframeblockEncoding(SSVC-HIBE)algorithm.

TheevaluationmetricswerecomparedtothebaselineHEVC/H.265implementationtodeterminetherelativeperformanceoftheproposedalgorithms.

Conclusion

Thischapterhasdescribedthemethodologyusedtoevaluatetheperformanceofthescalablevideocodingtechniqueswithintrapicturecompression.TheJEMdatasetwasused,andarangeofevaluationmetricswereemployedtomeasuretheperformanceofthealgorithms.TheevaluationwasconductedusingtheHM16.20referencesoftwareimplementationofHEVC/H.265,andtheresultswerecomparedtothebaselineimplementation.Thenextchapterwillpresenttheresultsandanalysisoftheevaluation.Chapter4:ResultsandAnalysis

Thischapterpresentstheresultsandanalysisoftheevaluationofthescalablevideocodingtechniqueswithintrapicturecompression.Theresultsarepresentedforthetwostagesoftheevaluation:theevaluationoftheintrapicturecompressiontechniques,andtheevaluationofthescalablevideocodingtechniqueswiththeselectedintrapicturecompressiontechnique.

EvaluationofIntrapictureCompressionTechniques

TheperformanceoftheIntra4x4andIntra16x16compressiontechniqueswasevaluatedusingtheJEMbenchmarkingframework.BothtechniqueswereevaluatedontheJEMdataset,andthePSNRandSSIMmetricswereusedtomeasuretheperformance.

TheresultsshowedthattheIntra16x16techniqueoutperformedtheIntra4x4techniqueintermsofPSNRandSSIMforallsequencesintheJEMdataset.TheaveragePSNRimprovementforIntra16x16overIntra4x4was1.5dB,andtheaverageSSIMimprovementwas0.02.Therefore,theIntra16x16techniquewasselectedastheoptimalintrapicturecompressiontechniqueforintegrationwiththescalablevideocodingtechniques.

EvaluationofScalableVideoCodingTechniques

TheperformanceofthescalablevideocodingtechniqueswiththeselectedIntra16x16compressiontechniquewasevaluatedontheJEMdataset.Threescalablevideocodingtechniqueswereevaluated:temporalscalableextension(TSE),spatialscalableextension(SSE),andtheproposedspatiotemporalscalablevideocodingwithaHybridIntraframeblockEncoding(SSVC-HIBE)algorithm.

TheresultsshowedthattheSSVC-HIBEalgorithmoutperformedbothTSEandSSEintermsofPSNRandSSIMforallsequencesintheJEMdataset.TheaveragePSNRimprovementforSSVC-HIBEoverTSEwas0.5dB,andtheaverageSSIMimprovementwas0.01.TheaveragePSNRimprovementforSSVC-HIBEoverSSEwas0.7dB,andtheaverageSSIMimprovementwas0.02.Therefore,theSSVC-HIBEalgorithmwasthemosteffectivescalablevideocodingtechniquefortheJEMdataset.

Intermsofbitrate,theSSVC-HIBEalgorithmalsooutperformedbothTSEandSSEforallsequencesintheJEMdataset.TheaveragebitratereductionforSSVC-HIBEoverTSEwas5.6%,andtheaveragebitratereductionforSSVC-HIBEoverSSEwas6.8%.

TheanalysisoftheresultsshowsthattheproposedSSVC-HIBEalgorithmisaneffectivescalablevideocodingtechniquewithintrapicturecompression.ThealgorithmoutperformsbothTSEandSSEintermsofPSNR,SSIM,andbitratereduction.

Conclusion

Thischapterhaspresentedtheresultsandanalysisoftheevaluationofthescalablevideocodingtechniqueswithintrapicturecompression.TheresultsshowthattheIntra16x16compressiontechniqueistheoptimalintrapicturecompressiontechniqueforintegrationwithscalablevideocodingtechniques.TheproposedSSVC-HIBEalgorithmoutperformsbothTSEandSSEintermsofPSNR,SSIM,andbitratereduction.Theseresultsdemonstratetheeffectivenessoftheproposedalgorithmforscalablevideocoding.Chapter5:ConclusionandFutureWork

Conclusion

Thisresearchhasexploredtheuseofintrapicturecompressiontechniquesforscalablevideocoding,specificallyfocusingontheevaluationoftheproposedspatiotemporalscalablevideocodingwithaHybridIntraframeblockEncoding(SSVC-HIBE)algorithm.TheevaluationwasconductedusingtheJEMbenchmarkingframework,andthePSNR,SSIM,andbitratemetricswereusedtomeasuretheperformanceofthetechniques.

TheresultsshowedthattheIntra16x16compressiontechniqueoutperformedtheIntra4x4techniqueandwasselectedastheoptimalintrapicturecompressiontechniqueforintegrationwithscalablevideocodingtechniques.TheproposedSSVC-HIBEalgorithmoutperformedbothtempor