scientific article
zbMath1282.62149MaRDI QIDQ2863747
Publication date: 3 December 2013
Full work available at URL: http://archiv.ub.uni-heidelberg.de/volltextserver/15609/1/thesis.pdf
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algorithmsimage filteringimage denoisingeigenvalue perturbation theoryefficient implementationBartlett's testnoise parameter estimationvariance-stabilizing transformationsAdditive white Gaussian noiseadditive white Gaussian noise removalanalysis of the block variance distributionanalysis of the grayvalue distributionCCD/CMOS noiseCCD/CMOS noise parameter estimationCCD/CMOS noise removalefficient implementationm image region selectioneigenvalue differenceestimators of the noise varianceexperiments with MeasTexexperiments with TID2008image block modelimage block subset selectionimage denoising methodsmeasurement of the accuracymethod based on image block selectionmodel-specific parameter estimationMRI noiseMRI noise removalMRI! noise parameter estimationnoise normality assessmentpopulation principal component analysispreclassiffcation of homogeneous image blockssample eigenvalue distributionsample principal component analysisSAR noiseSAR noise parameter estimationSAR noise removalselection of the VST parameterssignal-dependent noise parameter estimationsignal-dependent noise removalsignal-independent noise parameter estimationsignal-independent noise removalthe homogeneity assumptionthe signal and noise separationulrasound/film-grain noise removalultrasound/film-grain noiseultrasound/film-grain noise parameter estimationvariance of the sample covariance
Factor analysis and principal components; correspondence analysis (62H25) Image analysis in multivariate analysis (62H35) Research exposition (monographs, survey articles) pertaining to statistics (62-02)
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