cv.jpex: Bandwidth Selection and Noise Level Estimation

In DRIP: Discontinuous Regression and Image Processing

Bandwidth Selection and Noise Level Estimation

Description

Select the leave-one-out cross validation bandwidth for local linear kernel smoothing and estimates the noise level in the input image. Both the bandwidth parameter and the noise level are required inputs for the blind image deblurring procedure jpex.

Usage

cv.jpex(image, bandwidths, ncpus = 1)

Arguments

image	A blurry input image.
bandwidths	A vector of positive integers that specify the size of the neighborhood for local smoothing.
ncpus	The number of CPUs allocated for parallel computing.

Value

LLK	The estimated surface by local linear kernel (LLK) smoothing, using the CV selected bandwidth.
sigma	The estimated noise level, defined as the square root of the mean squared error (MSE) between LLK and the input image.
cv	A vector of the same length as that of the input bandwidths. Each element in the vector is the leave-one-out CV score associated with the corresponding bandwidth value.
bandwidth	The bandwidth parameters input by user.
band.min	The bandwidth parameter that results in the smallest CV score.

Author(s)

Yicheng Kang

References

Kang, Y. (2020) “Consistent Blind Image Deblurring Using Jump-Preserving Extrapolation”, Journal of Computational and Graphical Statistics, 29(2), 372 – 382, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/10618600.2019.1665536")}.

See Also

jpex

Examples

library(DRIP)
data(stopsign)
out <- cv.jpex(stopsign, c(2,3))

DRIP documentation built on May 29, 2024, 4:56 a.m.