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基于Contourlet变换与CS的彩色图像双重水印算法.docx

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基于Contourlet变换与CS的彩色图像双重水印算法 Introduction Withthewidespreaduseofdigitalimages,theissueofimagesecurityhasbecomeincreasinglyimportant.Imagewatermarkingisatechniquethataddsadigitalsignaturetoanimagetoprotectitfromunauthorizeduse.Thegoalofwatermarkingistoaddawatermarktoanimageinawaythatpreservestheimage'squalitywhilemakingitdifficultforanyonetoremoveormodifythewatermark.Inthispaper,wepresentadoublewatermarkingalgorithmthatusesContourletTransformandCompressiveSensing(CS)toembedtwowatermarksintoacolorimage. Background TheContourletTransformisamultiresolutiontechniquethatdecomposesanimageintoasetofsubbandsatdifferentscalesandorientations.Ithasbeenwidelyusedinimageprocessingapplicationssuchasdenoising,compression,andfeatureextraction.Themainadvantageofthecontourlettransformoverothertransformsisitsabilitytorepresentedgesandcontoursmoreaccurately. CompressiveSensing(CS)isasignalprocessingtechniquethatallowsfortheefficientacquisitionandreconstructionofsignals.ThekeyideabehindCSisthatmanysignalscanberepresentedbyasparseorcompressiblesetofcoefficients.CShasbeenappliedtovariousimageprocessingapplicationssuchasimagecompression,denoising,andreconstruction. Methodology Theproposeddoublewatermarkingalgorithmconsistsofthefollowingsteps: Step1:Pre-processingoftheHostImage ThehostimageisfirstconvertedfromRGBtoYCbCrcolorspace.TheYcomponent,whichrepresentstheluminanceoftheimage,isusedforwatermarking.Thechrominancecomponents(CbandCr)areusedforcolorrecovery. Step2:ContourletTransform TheYcomponentofthehostimageisdecomposedusingthecontourlettransform.Thecontourletcoefficientsaredividedintonon-overlappingblocksof4×4pixels.EachblockisthentransformedindependentlyusingtheDCT(DiscreteCosineTransform)toobtainthefrequencycoefficients. Step3:Watermarking Twowatermarksareaddedtothefrequencycoefficients.ThefirstwatermarkisabinaryimagethatisembeddedusingtheSpreadSpectrumtechnique.Thesecondwatermarkisareal-valuedimagethatisembeddedusingtheCompressiveSensingtechnique.TheSpreadSpectrumtechniqueaddsapseudo