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BrightnessEqualize
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BrightnessEqualize

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adjusts the brightness across image, correcting uneven illumination.

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BrightnessEqualize[image,flatfield]

uses the correction model given by flatfield, which models the variation in brightness across image.

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BrightnessEqualize[image,flatfield,darkfield]

uses the dark environment model given by darkfield.

Details and Options

  • Local brightness adjustment is also known as flat fielding, and is used for removing image artifacts caused by nonuniform lighting or variations in sensor sensitivities.
  • BrightnessEqualize works with arbitrary 2D and 3D images, adjusting the lightness channel in the LABColor space.
  • A flatfield image is an image of a homogeneous signal like a plain well-lit white background. A darkfield is the same image obtained without lighting. The flat fielding of an image with an object in the same setting is given by (image-darkfield)xMean[flatfield-darkfield]/(flatfield-darkfield).
  • Possible settings for either flatfield or darkfield include:
  • vala constant value val
    corrimagea correction image (rescaled to the image dimensions)
    {scope,model}fit the data into a given model
  • The default flatfield consists of a 2nd order polynomial fit. The default darkfield is assumed to be 0.
  • Using {scope,model}, the flatfield or darkfield is estimated by fitting a function.
  • The scope parameter specifies whether to fit the entire image data or the image projections along each axis. Possible settings include:
  • "Global"fit the entire image to the model
    "Marginal"separately fit model to the projections along each axis
  • The model can be one of the following:
  • nan n-degree polynomial
    f,params,varsan arbitrary model f with parameters params and variables vars
  • The following options are available:
  • Masking Automaticthe regions to use for model estimation
    PerformanceGoalAutomaticaspects of performance to try to optimize
  • Using Masking->Automatic, over- and underexposed pixels are not used for the adjustment.
  • With partially transparent images, the alpha channel is multiplied with the mask.

Examples

open allclose all

Basic Examples  (1)Summary of the most common use cases

Equalize brightness of a plain texture:

In[1]:=1
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https://wolfram.com/xid/0k77q04868l80-ff1a1q
Out[1]=1

Scope  (7)Survey of the scope of standard use cases

Data  (3)

Equalize a grayscale image of a scanned document:

In[206]:=206
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https://wolfram.com/xid/0k77q04868l80-dsousb
Out[206]=206

Adjust brightness in an unevenly illuminated color photo:

In[1]:=1
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https://wolfram.com/xid/0k77q04868l80-d0kvqh
Out[1]=1

Adjust brightness of a 3D CT scan image:

In[1]:=1
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https://wolfram.com/xid/0k77q04868l80-kbtbcx
Out[1]=1

Parameters  (4)

Remove uneven illumination in a microscopy image by estimating the brightness distribution:

In[1]:=1
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https://wolfram.com/xid/0k77q04868l80-lzehxr

Fitting a multivariate polynomial of first order on the entire image domain:

In[2]:=2
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https://wolfram.com/xid/0k77q04868l80-j0xc0
Out[2]=2

Using a second-order polynomial:

In[3]:=3
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https://wolfram.com/xid/0k77q04868l80-thkva
Out[3]=3

Fitting second-order univariate polynomials to the image marginals in each direction:

In[4]:=4
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https://wolfram.com/xid/0k77q04868l80-mmwx8t
Out[4]=4

Using a flatfield image:

In[1]:=1
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https://wolfram.com/xid/0k77q04868l80-dy11i3
Out[1]=1

Remove a vignette effect by fitting the lightness channel to a given model:

In[1]:=1
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https://wolfram.com/xid/0k77q04868l80-3fdnvg

Assuming a rotationally symmetric, radial-dependent vignette:

In[2]:=2
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https://wolfram.com/xid/0k77q04868l80-xagx2e
Out[2]=2

Assuming a Gaussian vignette:

In[3]:=3
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https://wolfram.com/xid/0k77q04868l80-6r7whd
Out[3]=3

Perform a subtractive correction on an astronomical image by estimating the dark field:

In[1]:=1
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https://wolfram.com/xid/0k77q04868l80-71r9lo
Out[1]=1

Options  (1)Common values & functionality for each option

Masking  (1)

By default, an automatic mask is used:

In[1]:=1
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https://wolfram.com/xid/0k77q04868l80-jtf2mm
In[2]:=2
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https://wolfram.com/xid/0k77q04868l80-o9d4js
Out[2]=2

Equalize brightness based on the image background:

In[3]:=3
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https://wolfram.com/xid/0k77q04868l80-gc48l9
Out[3]=3
In[4]:=4
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https://wolfram.com/xid/0k77q04868l80-6gbh1f
Out[4]=4

Applications  (7)Sample problems that can be solved with this function

Achieve a constant luminosity of the Moon surface:

In[1]:=1
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https://wolfram.com/xid/0k77q04868l80-00oqmx
In[2]:=2
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https://wolfram.com/xid/0k77q04868l80-b4e5t6
Out[2]=2

Equalize brightness of a microscopy image:

In[1]:=1
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https://wolfram.com/xid/0k77q04868l80-ybriqq

Identify the background:

In[2]:=2
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https://wolfram.com/xid/0k77q04868l80-ydlz3r
Out[2]=2

Equalize brightness distribution assuming a homogeneous background:

In[3]:=3
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https://wolfram.com/xid/0k77q04868l80-uifl9u
Out[3]=3

Equalize color distribution by handling each channel separately:

In[4]:=4
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https://wolfram.com/xid/0k77q04868l80-yohhw3
Out[4]=4

Remove uneven illumination from a scanned document:

In[1]:=1
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https://wolfram.com/xid/0k77q04868l80-82cqsh

Create a mask to omit text in the subsequent equilibration:

In[2]:=2
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https://wolfram.com/xid/0k77q04868l80-zxcuol
Out[2]=2

Equalize brightness distribution fitting a sixth-order polynomial:

In[3]:=3
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https://wolfram.com/xid/0k77q04868l80-xpmzd6
Out[3]=3

This improves the text recognition result:

In[4]:=4
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https://wolfram.com/xid/0k77q04868l80-x34x17
Out[4]=4

Equalize the brightness distribution without a mask applying a horizontal fit:

In[5]:=5
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https://wolfram.com/xid/0k77q04868l80-puyhto
Out[5]=5

This also improves the text recognition result:

In[6]:=6
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https://wolfram.com/xid/0k77q04868l80-blvhy0
Out[6]=6

Reduce the vignette effect of a photograph:

In[1]:=1
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https://wolfram.com/xid/0k77q04868l80-3o5jjy

Compute a mask for the background that is expected to have even illumination:

In[2]:=2
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https://wolfram.com/xid/0k77q04868l80-gjfqjd
Out[2]=2

Equalize image brightness:

In[3]:=3
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https://wolfram.com/xid/0k77q04868l80-cnvg48
Out[3]=3

Remove CCD artifacts from an image taken by a low-quality camera with many pixel defects.

Flat-field image of the camera:

In[1]:=1
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https://wolfram.com/xid/0k77q04868l80-mi6yvz

Microscopy image of a tear drop:

In[2]:=2
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https://wolfram.com/xid/0k77q04868l80-jortea

Flat-field correction:

In[3]:=3
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https://wolfram.com/xid/0k77q04868l80-xxeskf
Out[3]=3

Correct uneven illumination in an MR scan:

In[1]:=1
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https://wolfram.com/xid/0k77q04868l80-pze9w4

Use only muscle tissue for brightness estimation:

In[2]:=2
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https://wolfram.com/xid/0k77q04868l80-blucig
Out[2]=2
In[3]:=3
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https://wolfram.com/xid/0k77q04868l80-k3ee1n
Out[3]=3

Correct uneven brightness in a 3D magnetic resonance volume:

In[1]:=1
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https://wolfram.com/xid/0k77q04868l80-h0nqnl

Note the reduced brightness toward the perimeter of the volume:

In[2]:=2
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https://wolfram.com/xid/0k77q04868l80-sab1xl
Out[2]=2

Select the muscle tissue to estimate the brightness distribution:

In[3]:=3
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https://wolfram.com/xid/0k77q04868l80-v3hz0a
Out[3]=3
In[4]:=4
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https://wolfram.com/xid/0k77q04868l80-wr76u7
Out[4]=4

Estimate the brightness distribution by a polynomial in cylindrical coordinates of even orders up to 4:

In[5]:=5
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https://wolfram.com/xid/0k77q04868l80-6hjdzm

Compare the initial volume and the result with equalized brightness:

In[6]:=6
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https://wolfram.com/xid/0k77q04868l80-jzl7en
Out[6]=6
Wolfram Research (2017), BrightnessEqualize, Wolfram Language function, https://reference.wolfram.com/language/ref/BrightnessEqualize.html.
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Wolfram Research (2017), BrightnessEqualize, Wolfram Language function, https://reference.wolfram.com/language/ref/BrightnessEqualize.html.

Text

Wolfram Research (2017), BrightnessEqualize, Wolfram Language function, https://reference.wolfram.com/language/ref/BrightnessEqualize.html.

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Wolfram Research (2017), BrightnessEqualize, Wolfram Language function, https://reference.wolfram.com/language/ref/BrightnessEqualize.html.

CMS

Wolfram Language. 2017. "BrightnessEqualize." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/BrightnessEqualize.html.

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Wolfram Language. 2017. "BrightnessEqualize." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/BrightnessEqualize.html.

APA

Wolfram Language. (2017). BrightnessEqualize. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/BrightnessEqualize.html

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Wolfram Language. (2017). BrightnessEqualize. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/BrightnessEqualize.html

BibTeX

@misc{reference.wolfram_2025_brightnessequalize, author="Wolfram Research", title="{BrightnessEqualize}", year="2017", howpublished="\url{https://reference.wolfram.com/language/ref/BrightnessEqualize.html}", note=[Accessed: 22-March-2025 ]}

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@misc{reference.wolfram_2025_brightnessequalize, author="Wolfram Research", title="{BrightnessEqualize}", year="2017", howpublished="\url{https://reference.wolfram.com/language/ref/BrightnessEqualize.html}", note=[Accessed: 22-March-2025 ]}

BibLaTeX

@online{reference.wolfram_2025_brightnessequalize, organization={Wolfram Research}, title={BrightnessEqualize}, year={2017}, url={https://reference.wolfram.com/language/ref/BrightnessEqualize.html}, note=[Accessed: 22-March-2025 ]}

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@online{reference.wolfram_2025_brightnessequalize, organization={Wolfram Research}, title={BrightnessEqualize}, year={2017}, url={https://reference.wolfram.com/language/ref/BrightnessEqualize.html}, note=[Accessed: 22-March-2025 ]}