Compute difference between two one-sided LL2K
estimators along the gradient direction.
Usage
diffLL2K(image, bandwidth, plot)
Value
Returns a matrix of the estimated difference, \(|\widehat{f}_+ - \widehat{f}_-|\),
at each pixel.
Arguments
image
A square matrix object of size n by n, no
missing value allowed.
bandwidth
A positive integer to specify the number of
pixels used in the local smoothing.
plot
If plot = TRUE, an image of the difference at
each pixel is plotted.
Details
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 deblurring local linear kernel (LL2K) estimates are obtained in the
two half neighborhoods respectively.
References
Kang, Y., and Qiu, P., "Jump Detection in Blurred Regression
Surfaces," Technometrics, 56, 2014, 539-550.
data(sar) # SAR image is bundled with the package and it is a # standard test image in statistics literature.diff <- diffLL2K(image = sar, bandwidth = 6)