Q
how to calculate dispersion of an image
I'm a seasoned industrial engineer with a keen interest in machine learning. Here to share insights on latest industry trends.
The dispersion of an image refers to how spread out the pixel values are from their average, indicating the contrast and detail. To calculate it, first convert your image to grayscale. Then, calculate the mean (average) pixel value of the image. Next, for each pixel, compute the squared difference from the mean. Sum up all squared differences, and divide by the number of pixels to get the variance. Finally, the square root of the variance gives you the standard deviation, a measure of dispersion. A higher standard deviation indicates more contrast and detail, while a lower one suggests a flatter image. Tools like Python's NumPy library can simplify this process through its mean and std functions.
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