Using cloud confidence to create cloud mask from Landsat 8 QA_PIXEL

Question

I want to use the Landsat QA_PIXEl from this dataset to create a cloud mask in GEE. I only want to mask out the areas where there is high confidence that cloud cover is present. Looking at the documentation

Bits 8-9: Cloud Confidence
0: None
1: Low
2: Medium
3: High

However I do not understand very well the bitwiseAnd function in this context and so I'm not sure if what I'm doing is correct. Which I am guessing is not since I am not giving to the code the information that I only want to mask the High confidence pixels. Plus no image is rendered when I do this.

The code I'm doing for this part is this:

    def maskClouds(image):
        qa = image.select('QA_PIXEL')
        mask = qa.bitwiseAnd(1<<8).gt(2).Or(qa.bitwiseAnd(1<<9)).gt(2)
        return image.updateMask(mask)

How can I use the 'bitwiseAnd' function in this context and mask the "high" cloud confidence parts?

I have tried to do adapt my code to this question: Using cloud confidence to create cloud mask from Landsat 8 BQA? but this results in getting this error:

Image.rightShift: Bitwise operands must be integer only.

Answer 1

I think I found the solution for this.

def bitwiseExtract(input, fromBit, toBit):
  maskSize = ee.Number(1).add(toBit).subtract(fromBit)
  mask = ee.Number(1).leftShift(maskSize).subtract(1)
  return input.rightShift(fromBit).bitwiseAnd(mask)

qa = image.select('QA_PIXEL')
cloudQualityMask = bitwiseExtract(qa, 8, 9)
cloud_mask = qa.bitwiseAnd(cloud_shadow_bit_mask).lt(3)
imageMasked = image.updateMask(cloud_mask)