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I am trying to view a tif satellite image which has 4 bands. I want to remove the last band (NIR) and view the RGB image only, so I am trying to split the NIR from the rest of the image. Here is my code

import rasterio
from rasterio.plot import show
from matplotlib import pyplot as plt
from rasterio import plot
import numpy as np
#to display RGB
dataset = rasterio.open('2.tif')
%matplotlib inline
plot.show(dataset.read([1,2,3]), cmap="gray")
#to display just the red band
%matplotlib inline
plot.show(dataset.read(4), cmap="gray")

I provided a screen shot of the code and the output I am getting enter image description here

Displaying just 1 band seems fine, but any idea why I keep seeing an image with a yellow and white color scheme when I try to display RGB bands together? I thought it's a cmap issue at the beginning, but even when I add 'cmap="gray"' the color of the image remains the same.

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Reading and plotting works just fine, but the problem is in the warning you get from matplotlib:

  • If an image has integer values matplotlib will clip them to interval [0, 255]
  • If an image has float values matplotlib will clip them to interval [0, 1.0]

In your case all values were clipped to either 255 or to 1.0 and that is why you see a white image. Also note that this happens only when you try to plot a RGB image. When plotting an image with a single channel matplotlib won't do any clipping.

Solution - check dtype of your image values and decrease / change them accordingly. Example:

image = dataset.read([1,2,3])
print(image.dtype, np.max(image))
image = (255 * image / np.max(image)).astype(np.uint8)
plot.show(image)

This transforms image values to integer values from [0, 255]. (Instead by multiplying images by 255 / np.max(image) you might want to try some other constant to get nicer image. I used this one because I don't know anything about values of your image.)

  • Thank you for your answer. I'm not sure if I understand correctly. I tried your code above, and I replaced 255 with the maximum value of my image's data (uint16 --> 1286). But the image that I am getting is too distorted. Edit: I also tried 65535 but I am getting a completely black/dark gray image – Nour Dec 23 '18 at 9:51
  • If you are working with integer values, you just have to make sure your values are properly scaled from 0 to 255. How you scale them is up to you. Scaling them up to 1286 or 65535 probably won't show correct image. – AleksMat Dec 28 '18 at 9:31

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