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entropy

Entropy of grayscale image

Syntax

e = entropy(I)

Description

example

e = entropy(I) returns e, a scalar value representing the entropy of grayscale image I.

Examples

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Read image into the workspace.

I = imread('circuit.tif');

Calculate the entropy.

J = entropy(I)
J = 6.9439

Input Arguments

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Grayscale image, specified as a real, nonsparse numeric array. I can have any dimension. If I has more than two dimensions, entropyfilt treats it as a multidimensional grayscale image and not as a truecolor (RGB) image.

Data Types: double | uint8 | uint16 | uint32 | logical

Output Arguments

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Entropy of image I, returned as a numeric scalar.

Data Types: double

More About

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Entropy

Entropy is a statistical measure of randomness that can be used to characterize the texture of the input image.

Entropy is defined as -sum(p.*log2(p)), where p contains the normalized histogram counts returned from imhist.

Tips

  • By default, entropy uses two bins for logical arrays and 256 bins for uint8, uint16, or double arrays. entropy converts any class other than logical to uint8 for the histogram count calculation so that the pixel values are discrete and directly correspond to a bin value.

References

[1] Gonzalez, R.C., R.E. Woods, S.L. Eddins, Digital Image Processing Using MATLAB, New Jersey, Prentice Hall, 2003, Chapter 11.

Introduced before R2006a

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