Applying a mask on another mask (or AND condition) for image analysis

Question

I'm trying to do an AND operation on two masks to get their co-positive pixels but it doesn't seem to work - I get the original mask somehow after the AND operation:

plt.imshow(mask);plt.show()
plt.imshow(other_mask);plt.show()
masked_both = cv2.bitwise_and(mask, other_mask)
plt.imshow(masked_both);plt.show()

What's the right way to do it? Thanks

Answer 1

Is is most likely that other_mask contains only positive values, but imshow scales the values. For example, min value of other_mask can be 100 and displayed as purple, and max value can be 200 and displayed as yellow. In that case masked_both will be the same as mask. You can check this by inspecting min and max values of your masks.

If this is the case, you can fix it by normalizing value ranges of both masks:

min_value = mask.min()
max_value = mask.max()
masked_normalized = (mask - min_value) / (max_value - min_value)