How to Convert Number Ranges in Python While Preserving Ratios?

Converting Number Ranges with Ratio Preservation in Python

In image processing, it's often necessary to convert the pixel values from one range to another, while maintaining the relative ratios between the points. This conversion ensures that important features and details are preserved despite a change in the numeric representation.

To achieve this ratio-preserving conversion, we can employ the following formula:

NewValue = (((OldValue - OldMin) * (NewMax - NewMin)) / (OldMax - OldMin)) + NewMin

Breaking down the formula:

• OldValue: The original pixel value within the old range.
• OldMin: The minimum value in the old range.
• OldMax: The maximum value in the old range.
• NewMax: The maximum value in the new range (e.g., 100).
• NewMin: The minimum value in the new range (e.g., 0).

For example, if you have a pixel value of -5000.00 in an image with a range of -16000.00 to 16000.00, and you want to convert it to the range 0 to 100, the new value would be:

NewValue = (((-5000.00 - (-16000.00)) * (100 - 0)) / (16000.00 - (-16000.00))) + 0
NewValue = 31.25

This new value of 31.25 maintains the same relative position in the new range as the original value in the old range.

You can further customize this formula by adjusting the NewMin and NewMax values to accommodate specific requirements (e.g., changing the target range to -50 to 800).

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