CLAHE | R Documentation |
CLAHE
performs adaptive histogram equalization to enhance
the contrast of an image. Unlike regular histogram equalization
(histEq
), CLAHE first divides the image into small blocks
called "tiles" and performs histogram equalization on each of these tiles.
To reduce noise amplification contrast limiting is also applied: if any
histogram bin is above the specified contrast limit, those pixels are
clipped and distributed uniformly to other bins before applying histogram
equalization. After equalization, to remove artifacts in tile borders,
bilinear interpolation is applied.
CLAHE(image, clip_limit = 40, n_tiles = c(8, 8), target = "new")
image |
An |
clip_limit |
A numeric value representing the contrast limit above which pixels are clipped and distributed uniformly to other bins before applying histogram equalization on the tiles. |
n_tiles |
A vector with 2 elements representing the number of tiles
along the width and height of the image (default: |
target |
The location where the results should be stored. It can take 3 values:
|
If target="new"
, the function returns an Image
object. If target="self"
, the function returns nothing and modifies
image
in place. If target
is an Image
object,
the function returns nothing and modifies that Image
object in
place.
Simon Garnier, garnier@njit.edu
Image
, histEq
balloon <- image(system.file("sample_img/balloon1.png", package = "Rvision"))
balloon_Lab <- changeColorSpace(balloon, "Lab")
L <- extractChannel(balloon_Lab, 1)
clahe <- CLAHE(L, 1, c(2, 2))
insertChannel(balloon_Lab, 1, clahe)
balloon_contrast <- changeColorSpace(balloon_Lab, "BGR")
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