entropy() - Image Processing

E = entropy(I) returns E,
a scalar value representing the entropy of grayscale image I.
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 histogram counts returned
from imhist. By default, entropy uses
two bins for logical arrays and 256 bins for uint8, uint16,
or double arrays.I can be a multidimensional image. If I has
more than two dimensions, the entropy function
treats it as a multidimensional grayscale image and not as an RGB
image.

Syntax

E = entropy(I)

Example

-sum(p.*log2(p))

Output / Return Value

Limitations

Alternatives / See Also

Reference