cvwavelet.image.after.impute {CVThresh}R Documentation

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.


[Package CVThresh version 1.0.5 Index]