简介:Recently,Changetal.proposedaSudoku-basedsecretimagesharingscheme.TheyutilizedtheSudokugridtogeneratemeaningfulshadowimages,andtheirschemesatisfiedallessentialrequirements.BasedonChangetal.'sscheme,weproposeanovel(n,n)secretimagesharingschemebasedonSudoku.Intheproposedscheme,asecretimagecanbesharedamongndifferentcoverimagesbygeneratingnshadowimages,andthesecretimagecanbereconstructedwithoutdistortionusingonlythesenshadowimages.Also,theproposedschemecansolvetheoverflowandunderflowproblems.Theexperimentalresultsshowthatthevisualqualityoftheshadowimagesissatisfactory.Furthermore,theproposedschemeallowsforalargeembeddingcapacity.
简介:ThepreparationofPT/PEK-cfilmsisreportedaswellastheirdielectricandopticalproperties.Thec-axisorientationratioofthefilmsis68%.Dielectricconstantandlossfactorat10kHzisabout4.023F/mand0.003,respectively.Therefractiveindicesofthefilms,neandno,are1.6573and1.6278at0.63μmwavelength,respectively.Theopticalband-gapofthefilmwithathicknessof2.33μmisfoundtobe3.06eV
简介:InviewofthelimitationsofaRn-GnmodelinthelowfrequencyrangeandthedefectsofanEn-Inmodelincommonusenow,thispaperbuildsacompleteEn-Inmodelaccordingtothetheoryofrandomharmonic.Theparametersforthelow-noisedesignsuchastheequivalentinputnoisyvoltageEns,theoptimumsourceimpedanceZsoptandtheminimumnoisefigureFmincanbecalculatedaccuratelybyusingthisEn-Inmodelbecauseitconsidersthecoherencebetweenthenoisesourcesfully.Moreover,thispaperpointsoutthatitwillcausethemaximum30%miscalculationwhenneglectingtheeffectsofthecorrelationcoefficient7.Usingtheseries-seriescircuitsasanexample,thispaperdiscussesthemethodsfortheEn-InnoiseanalysisofelectroniccircuitspreliminarilyanddemonstratesitscorrectnessthroughthecomparisonbetweenthesimulatedandmeasuredresultsoftheminimumnoisefigureFminofasinglecurrentseriesnegativefeedbackcircuit.
简介:传统图像局部方向特性的自适应全变分去噪算法,通过计算图像局部方向的角度矩阵,用优化最小化算法迭代求解实现图像去噪,不能保存图像边缘信息,去噪效果及稳定性差。提出基于能量回归滤波全变分图像自适应去噪算法,通过能量回归尺度空间滤波法获取滤波图像时,对源噪声图像进行多尺度二进小波分解获取小波变换系数及低频粗糙分量,采用能量回归滤波法计算小波系数并对小波系数进行重构,获取源图像的滤波图像。采用基于图像局部方向特性的自适应全变分去噪算法从含噪滤波图像中分离出轮廓尺度图像,对含噪图像同轮廓尺度图像实施差计算获取含噪残差纹理细节图像,基于该图像运算获取规整化可信度参数λ后,采用基于参数P与λ的全变分图像自适应去噪算法对带噪滤波图像进行处理,得到消噪图像。实验结果表明:所提算法去噪效果佳,其具有较高的稳定性和效率。