denoise {EBImage} | R Documentation

## Enhancing image and image colors

### Description

Functions to enhance image colours.

### Usage

        denoise(x, r=0, ...)
        mediansmooth(x, r=2, ...)
        despeckle(x, ...)

        sharpen(x, r=0, s=0.5, ...)
        umask(x, r=0, s=0.5, amount=5, t=2, ...)

        blur(x, r=0, s=0.5, ...)
        gblur(x, r=0, s=0.5, ...)

        noise(x, type="gaussian", ...)

### Arguments

`x`
  An object of `Image-class`.
`r`
  The radius of the pixel neighbourhood to take into account. The 0 value enables automatic radius selection.
`s`
  The standard deviation of the Laplacian (`sharpen`) or Gaussian (`umask, blur, gblur`), in pixels. For reasonable results of most functions, `r` must be larger than `s`.
`amount`
  The percentage of the difference between the original and the blur image that is added back into the original.
`t`
  The threshold in pixels needed to apply the diffence amount.
`type`
  The type of noise to add.
`...`
  Reserved for future use.

### Value

A transformed image in an object of `Image-class`.

### Details

`despeckle` reduces the speckle noise.

`mediansmooth` smoothes a noisy image by replacing each pixel value by the median in a set of neighbouring pixels as defined by radius.

`blur, gblur` blur an image. `blur` differs from Gaussian blur, `gblur`, in that it uses a separable kernel which is faster but mathematically equivalent to the non-separable kernel (implemented in `ImageMagick`).

`sharpen, umask` sharpen an image. `umask` uses the unsharp mask algorithm. The the image is convolved with a Gaussian operator of the given radius and standard deviation, `s`.

`noise` adds noise to an image. Supported noise types are: `'uniform', 'gaussian'` (default) `, 'multi', 'impulse', 'laplace'` and `'poisson'`.

### Author(s)

Copyright (c) 2005-2006 Oleg Sklyar : osklyar@ebi.ac.uk

### References

ImageMagick: http://www.imagemagick.org.

### See Also

`Image-class`

[Package EBImage version 2.0.1 Index]