CVThresh (version 1.1.0)

cvwavelet.image.after.impute: 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

Value

• Reconstruction of images and thresholding values by level-dependent cross-validation
• imagecv
  reconstruction of images
• cvthresh
  thresholding values by level-dependent cross-validation

Details

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

See Also

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