JPLLK_surface {DRIP} | R Documentation |
Estimate surface using piecewise local linear kernel smoothing. Bandwidth is chosen by leave-one-out cross validation.
JPLLK_surface(image, bandwidth, plot = FALSE)
image |
A square matrix object of size n by n, no missing value allowed. |
bandwidth |
A numeric vector with positive integers, which specify the number of pixels used in the local smoothing. The final fitted surface chooses the optimal bandwidth from those provided by users. |
plot |
If plot = TRUE, the image of the fitted surface is plotted |
At each pixel, the gradient is estimated by a local linear
kernel smoothing procedure. Next, the local neighborhood is
divided into two halves along the direction perpendicular to
(\widehat{f}'_{x}
, \widehat{f}'_{y}
). Then the one-
sided local linear kernel (LLK) estimates are obtained in the
two half neighborhoods respectively. Among these two one-sided
estimates, the one with smaller weighted mean square error is
chosen to be the final estimate of the regression surface at the
pixel.
A list of fitted values, residuals, chosen bandwidth and estimated sigma.
Qiu, P., "Jump-preserving surface reconstruction from noisy data", Annals of the Institute of Statistical Mathematics, 61(3), 2009, 715-751.
data(sar) # SAR image is bundled with the package and it is a
# standard test image in statistics literature.
fit = JPLLK_surface(image=sar, bandwidth=c(3, 4))