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Why gray to BGR conversion giving distorted results

asked 2017-12-21 23:52:03 -0500

Nilushika gravatar image

I used cvtColor for converting int16 2D numpy array into BGR color image. But when view it via imshow() it giving distorted picture. Here is the code snippet i made conversion.

import cv2 as cv

color_image = cv.cvtColor(np.float32(ct_scan), cv.COLOR_GRAY2BGR)
plt.imshow(color_image)
plt.show()

plt.imshow(np.float32(ct_scan),cmap=plt.cm.gray)
plt.show()

The source image, ct_scan is a int16 2D numpy array. The conversion of ct_scan into float32 was done to compatible with the cvtColor function. The results are showing in figure 1-The converted color image and figure 2-source image converted to float32 dtype

But as you can see the converted image is distorted. Can you please help to identify the error behind, or suggest a method to convert the 2D numpy array to a color image.

image description First image image description Second image

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note, that your image is still in the 16bit range, while matplotlib probably expects something in [0..1] for float images. try to divide by 0xffff before that

berak gravatar imageberak ( 2017-12-22 02:49:07 -0500 )edit

Thanks berak

Nilushika gravatar imageNilushika ( 2017-12-22 22:21:46 -0500 )edit

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answered 2017-12-22 00:39:15 -0500

moHe gravatar image

Firstly, you'd better know the gray transformation between gray and rgb: Gray_value = 0.299R + 0.587G + 0.114B, so the transformation is not reversible, the reverse convertion is probably that each channel take the 1/3 of gray value.

Then the convertion may cause information loss due to the format transformation, as I thought.

Hope this can inspire you:)

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Thanks moHe. But the same conversion not giving bad results for images like Cameraman

Nilushika gravatar imageNilushika ( 2017-12-22 02:13:26 -0500 )edit
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Asked: 2017-12-21 23:52:03 -0500

Seen: 362 times

Last updated: Dec 22 '17