blurImage: Apply a blurring filter
In karenkuang37/MyoManager: Visual analysis of skeletal muscle microscopy data

Description Usage Arguments Value References Examples

The following function uses makeBrush to generate a filter of choice and applies it to the image. Blurring tends to be useful prior to analyzing individual objects in an image with ill-defined edges and/or uneven intensities.

blurImage(
  img,
  brush_size = 5,
  brush_shape = c("box", "disc", "diamond", "Gaussian", "line"),
  sigma = 0.3
)

`img`	An object of Image class specific to EBImage, stored as multi- dimensional arrays containing the pixel intensities.
`brush_size`	A `numeric` value containing the size of the brush in pixels. This should be an odd number; even numbers are rounded to the next odd one, i.e., size = 4 has the same effect as size = 5. Default is 5.
`brush_shape`	A `character` vector indicating the shape of the brush. Can be box, disc, diamond,Gaussian or line. Default is box.
`sigma`	An optional numeric containing the standard deviation of the Gaussian shape.This argument is relevant only for the Gaussian brush shape.Default is 0.3.

A blurred version of the input image.

Gregoire Pau, Florian Fuchs, Oleg Sklyar, Michael Boutros, and Wolfgang Huber (2010): EBImage - an R package for image processing with applications to cellular phenotypes. Bioinformatics, 26(7), pp. 979-981, link (https://bioconductor.org/packages/release/bioc/html/EBImage.html

# Example 1
# select nuclei channel in a tiff file
mouse = loadImage(system.file('extdata/Mouse_01.tiff', package='MyoManager'))
mNuc = selectFrame(mouse,3)
viewImage(mNuc)

# apply the blurring brush
img_blur <- blurImage(mNuc, 11, 'gaussian', sigma = 5)

# visualize blurred nuclei - brightening is optional (for display purpose)
viewImage(intensityCtrl(img_blur, 0, 3))

# Example 2
rabbit = loadImage(system.file('extdata/Rabbit_01.tif', package='MyoManager'))
rNuc = selectFrame(rabbit, 3)
viewImage(rNuc)
img_blur = blurImage(rNuc, 11, 'line')
viewImage(img_blur)