Opencv + Python cv2.imwrite() and cv.imshow both images present different output

Question

I am using Opencv(3.0) and Python 2.7 to do image processing, but I have an issue with cv2.imwrite() and cv2.imshow() . They produce different output, my code is as below:

tfinal = (255)*(nir_img-red_img)/(nir_img+red_img)
cv2.imwrite(_db_img1+'_NDVI'+_ext_img,tfinal)
cv2.imshow('NDVI',tfinal)

First image is output of cv2.imshow()

Second image is output of cv2.imwrite()

Answer 1

This can happen because of your data type. imwrite and imshow determine what to do with your data automatically, relaying on datatype. As said in documentation for imwrite and imshow :

imwrite :

The function imwrite saves the image to the specified file. The image format is chosen based on the filename extension (see imread() for the list of extensions). Only 8-bit (or 16-bit unsigned (CV_16U) in case of PNG, JPEG 2000, and TIFF) single-channel or 3-channel (with 'BGR' channel order) images can be saved using this function.

imshow :

The function may scale the image, depending on its depth:

• If the image is 8-bit unsigned, it is displayed as is.
• If the image is 16-bit unsigned or 32-bit integer, the pixels are divided by 256. That is, the value range [0,255*256] is mapped to [0,255].
• If the image is 32-bit floating-point, the pixel values are multiplied by
  255. That is, the value range [0,1] is mapped to [0,255].

So, it seems that your underlying data type is not unsigned char, but float or 32-bit integer.

Also because of operation priorities you can run into troubles with:

(255)*(nir_img-red_img)/(nir_img+red_img)

You can run into overflow. It will be better to set values in range of [0; 1] and than multiply them:

(255) * ( (nir_img-red_img)/(nir_img+red_img) )

Answer 2

Thanks to Melnikov Sergei for a brief introduction regarding mine solution. I have resolved this using below syntax modified in my program. when I am writing my image multiplied with 255 and I'm getting the same result.

tfinal = (255)*(nir_img-red_img)/(nir_img+red_img)
cv2.imwrite(_db_img1+'_NDVI'+_ext_img,tfinal*255)
cv2.imshow('NDVI',tfinal)