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RandomImage[max]

gives an image with pseudorandom pixel values in the range 0 to max.

RandomImage[{min,max}]

generates pseudorandom pixel values in the range min to max.

RandomImage[dist]

generates pixel values using a symbolic distribution dist.

RandomImage[…,size]

generates a random image of the specified size.

RandomImage[…,size,"type"]

gives an image converted to the specified type.

Details and Options
Details and Options Details and Options
Examples  
Basic Examples  
Scope  
Distribution  
Size  
Type  
Options  
ColorSpace  
ImageSize  
Applications  
Properties & Relations  
Possible Issues  
Neat Examples  
See Also
Related Guides
History
Cite this Page

RandomImage

RandomImage[max]

gives an image with pseudorandom pixel values in the range 0 to max.

RandomImage[{min,max}]

generates pseudorandom pixel values in the range min to max.

RandomImage[dist]

generates pixel values using a symbolic distribution dist.

RandomImage[…,size]

generates a random image of the specified size.

RandomImage[…,size,"type"]

gives an image converted to the specified type.

Details and Options

  • RandomImage gives an image where pixel values are drawn from a specified distribution. The pixel values are not correlated spatially.
  • Random images can be used for creating synthetic noise images and image effects.
  • RandomImage by default gives an image of a real type.
  • RandomImage[] is equivalent to RandomImage[1,{150,150}].
  • RandomImage[…] is equivalent to RandomImage[…,{150,150}].
  • The size specification can be one of the following:
  • side2D image of size {side,side}
    {width,height}2D image size specification
    {width,depth,height}3D image size specification
  • Possible settings for "type" include:
  • "Bit"integer 0 or 1
    "Byte"integer 0 through 255
    "Bit16"integer 0 through 65535
    "Real32"single-precision real (32 bit)
    "Real64"double-precision real (64 bit)
  • RandomImage accepts all Image and Image3D options with the following additions and modifications:
  • ColorSpace Automaticgenerates an image of the specified color space
    InterleavingNonewhether to generate an interleaved image

Examples

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Basic Examples  (3)

Generate a random image:

Generate a random RGB image:

Generate a random 3D image:

Scope  (8)

Distribution  (5)

By default, pixel values range from 0 to 1:

Specify a range of pixel values:

Generate an image from pseudorandom values in the range 0 to :

A random image from a normal distribution:

Generate a 4-channel image using some multivariate distribution:

Size  (2)

By default, a 2D image is generated:

Specify the image dimensions for a square image:

Specify the image dimensions:

Specify the 3D image dimensions:

Type  (1)

By default a real image is created:

Create a byte image:

Options  (5)

ColorSpace  (4)

By default, no explicit color space is assumed:

Generate a "Grayscale" image:

Generate a random "RGB" image:

Generate an "HSB" image using some univariate distribution:

Generate a "LAB" image using a multivariate uniform distribution with specific bounds:

ImageSize  (1)

By default, the image is created with ImageSize->Automatic:

Specify the display size:

Applications  (4)

Additive noise:

Multiplicative noise:

Image of Laplacian noise:

RGB image simulating salt-and-pepper noise using a heavy-tail distribution:

Properties & Relations  (7)

Generate an image with constant intensity:

Use the specialized function ConstantImage instead:

Generate the random data using RandomReal:

Generate a random binary image using RandomInteger:

Generate the random data using RandomVariate:

In a uniformly random image, neighboring pixels are not correlated:

After local filtering, pixel values drawn from the original distribution are spatially correlated:

Create an image with pixels randomly chosen from a list of colors:

Create an image from colors randomly chosen from a convex hull defined by a list of colors:

Possible Issues  (1)

Out-of-range pixel values are rendered as black or white:

Use ImageAdjust to see the full range of values:

Neat Examples  (1)

Show the effect of various types of noise: original image, Poisson noise, uniform noise, Gaussian noise, Laplacian noise, salt-and-pepper noise:

Wolfram Research (2010), RandomImage, Wolfram Language function, https://reference.wolfram.com/language/ref/RandomImage.html (updated 2020).

Text

Wolfram Research (2010), RandomImage, Wolfram Language function, https://reference.wolfram.com/language/ref/RandomImage.html (updated 2020).

CMS

Wolfram Language. 2010. "RandomImage." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2020. https://reference.wolfram.com/language/ref/RandomImage.html.

APA

Wolfram Language. (2010). RandomImage. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/RandomImage.html

BibTeX

@misc{reference.wolfram_2025_randomimage, author="Wolfram Research", title="{RandomImage}", year="2020", howpublished="\url{https://reference.wolfram.com/language/ref/RandomImage.html}", note=[Accessed: 01-May-2026]}

BibLaTeX

@online{reference.wolfram_2025_randomimage, organization={Wolfram Research}, title={RandomImage}, year={2020}, url={https://reference.wolfram.com/language/ref/RandomImage.html}, note=[Accessed: 01-May-2026]}