DRIP (version 2.0)

jpex: Blind Image Deblurring

Description

Take in any square matrix (noisy blurry image) and deblur it.

Usage

jpex(image, bandwidth, alpha, sigma)

Value

deblurred

A square matrix representing the deblurred image.

edge

A square matrix, the element of which is the value of the Chi-square test statistic at a pixel location. One can classify a given pixel as a blurry pixel if edge[i, j] > qchisq(1 - alpha, 2).

Arguments

image

A square matrix representing a blurry image.

bandwidth

A positive integer that specifies the size of the neighborhood for local smoothing.

alpha

A numeric between 0 and 1. This is the significance level for the Chi-square hypothesis test. The null hypothesis is that a given pixel is in a continuity region and not affected by the blur.

sigma

A positive numeric value for the noise level in the blurred image. It is used in the Chi-square test.

Author

Yicheng Kang

References

Kang, Y. (2020) ``Consistent Blind Image Deblurring Using Jump-Preserving Extrapolation'', Journal of Computational and Graphical Statistics, 29(2), 372 -- 382, tools:::Rd_expr_doi("10.1080/10618600.2019.1665536").

See Also

cv.jpex

Examples

library(DRIP)
data(stopsign)
out <- jpex(image = stopsign, bandwidth = as.integer(2), sigma =
0.00623, alpha = 0.001)