stepEdgeParSelLC2K: edge detection, parameter selection

In DRIP: Discontinuous Regression and Image Processing

edge detection, parameter selection

Description

Select bandwidth and threshold value for LC2K edge detector using bootstrap procedure

Usage

stepEdgeParSelLC2K(image, bandwidth, thresh, nboot)

Arguments

image	A square matrix object of size n by n, no missing value allowed.
bandwidth	Positive integers to specify the number of pixels used in the local smoothing. These are the bandwidth parameters to be chosen from.
thresh	Threshold values to be chosen from.
nboot	Number of bootstrap samples.

Details

A jump-preserving local linear kernel smoothing is applied to estimate the discontinuous regression surface; Bootstrap samples are obtained by drawing with replacement from the residuals and the d_{KQ} is computed for the detected edges of the original sample and those of the bootstrap samples.

Value

Returns a list of the selected bandwdith, the selected threshold value, and a matrix of d_{KQ} values with each entry corresponding to each combination of bandwdith and threshold.

References

Kang, Y., and Qiu, P., "Jump Detection in Blurred Regression Surfaces," Technometrics, 56, 2014, 539-550.

See Also

stepEdgeParSelLCK, stepEdgeParSelLLK, stepEdgeParSelLL2K, stepEdgeLC2K

Examples

data(sar) # SAR image is bundled with the package and it is a
          # standard test image in statistics literature.
#parSel = stepEdgeParSelLC2K(image=sar, bandwidth=4:5, thresh=
#19:20, nboot=10) # Time consuming

DRIP documentation built on April 7, 2022, 1:06 a.m.