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").