data171 - entropy

Data visualization over time

Monthly Maximum

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Monthly Minimum

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Monthly Standard Deviation

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Entropy

Entropy is typically calculated from the image histogram, which represents the frequency distribution of pixel intensity levels. When an image has a uniform distribution of intensity levels, meaning all intensity levels are equally probable, entropy will be high, as there is more uncertainty or disorder in the pixel distribution. Conversely, if an image has a highly skewed or concentrated distribution of intensity levels, entropy will be low, as there is less uncertainty or disorder in the pixel distribution. When an image is very diverse, this generally implies low entropy.