| jpex {DRIP} | R Documentation |
Blind Image Deblurring
Description
Take in any square matrix (noisy blurry image) and deblur it.
Usage
jpex(image, bandwidth, alpha, sigma)
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. |
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
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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, doi:10.1080/10618600.2019.1665536.
See Also
Examples
library(DRIP)
data(stopsign)
out <- jpex(image = stopsign, bandwidth = as.integer(2), sigma =
0.00623, alpha = 0.001)