cvwavelet.image.after.impute {CVThresh}

Cross-Validation Wavelet Shrinkage for two-dimensional data after imputation

Description

This function performs level-dependent cross-validation wavelet shrinkage for two-dimensional data given the cross-validation scheme and imputation values.

Usage

cvwavelet.image.after.impute(images, imagewd, imageimpute,
   cv.index1=cv.index1, cv.index2=cv.index2,
   cv.optlevel=cv.optlevel, cv.tol=cv.tol, cv.maxiter=cv.maxiter,
   filter.number=2, ll=3)

Arguments

images

noisy image

imagewd

two-dimensional wavelet transform

imageimpute

two-dimensional imputed values according to cross-validation scheme

cv.index1

test dataset row index according to cross-validation scheme

cv.index2

test dataset column index according to cross-validation scheme

cv.optlevel

thresholding levels

cv.tol

tolerance for cross-validation

cv.maxiter

maximum iteration for cross-validation

filter.number

specifies the smoothness of wavelet in the decomposition (argument of WaveThresh)

ll

specifies the lowest level to be thresholded

Details

Calculating thresholding values and reconstructing noisy image given cross-validation scheme and imputation.

Value

Reconstruction of images and thresholding values by level-dependent cross-validation

imagecv

reconstruction of images

cvthresh

thresholding values by level-dependent cross-validation

See Also

cvwavelet.image, cvtype.image, cvimpute.image.by.wavelet.